{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## This experiment was performed using LightFM which a very popular recommender module and it has support to take in different data modalities such as text, image, graphical, etc. Please check out their official documentation in the link mentioned below:  \nLink to LightFM:\nmaking.lyst.com/lightfm/docs/home.html  \n\nIt also incorporates Multiprocessing to process predictions for final users\n\nPlease refer to the previous notebooks for different alterations. Summary of the alterations:  \n1. Train Light FM without making use of any customer or article based feature on whole dataset. --> (https://www.kaggle.com/rickykonwar/h-m-lightfm-nofeatures)  \n2. Train Light FM by making use of 1 article based feature on whole dataset --> Current Version  \n3. Train Light FM by making use of 2 article based feature on whole dataset --> To Do\n4. Train Light FM by making use of multiple article based features and also 1 customer based feature on whole dataset --> To Do\n\nHope you like this notebook, please feel free to vote for this notebook","metadata":{}},{"cell_type":"markdown","source":"## Importing Required Libraries","metadata":{}},{"cell_type":"code","source":"# Importing Libraries\nimport sys, os\nimport re\nimport tqdm\nimport time\nimport pickle\nimport random\nimport itertools\n\nimport pandas as pd\nimport numpy as np\nimport scipy.sparse as sparse\n%matplotlib inline\nimport matplotlib.pyplot as plt\n\n# lightfm \nfrom lightfm import LightFM\nfrom lightfm.evaluation import precision_at_k\nfrom lightfm.cross_validation import random_train_test_split\n\n# multiprocessing for inferencing\nfrom multiprocessing import Pool","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:23:52.128948Z","iopub.execute_input":"2022-03-15T13:23:52.129591Z","iopub.status.idle":"2022-03-15T13:23:52.258503Z","shell.execute_reply.started":"2022-03-15T13:23:52.129497Z","shell.execute_reply":"2022-03-15T13:23:52.257528Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"os.environ[\"openblas_set_num_threads\"] = \"1\"\ndata_path = r'../input/h-and-m-personalized-fashion-recommendations/transactions_train.csv'\ncustomer_data_path = r'../input/h-and-m-personalized-fashion-recommendations/customers.csv'\narticle_data_path = r'../input/h-and-m-personalized-fashion-recommendations/articles.csv'\nsubmission_data_path = r'../input/h-and-m-personalized-fashion-recommendations/sample_submission.csv'","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:24:01.692648Z","iopub.execute_input":"2022-03-15T13:24:01.693488Z","iopub.status.idle":"2022-03-15T13:24:01.698249Z","shell.execute_reply.started":"2022-03-15T13:24:01.693447Z","shell.execute_reply":"2022-03-15T13:24:01.697419Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Data Extraction\ndef create_data(datapath, data_type=None):\n    if data_type is None:\n        df = pd.read_csv(datapath)\n    elif data_type == 'transaction':\n        df = pd.read_csv(datapath, dtype={'article_id': str}, parse_dates=['t_dat'])\n    elif data_type == 'article':\n        df = pd.read_csv(datapath, dtype={'article_id': str})\n    return df","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:24:02.065300Z","iopub.execute_input":"2022-03-15T13:24:02.065879Z","iopub.status.idle":"2022-03-15T13:24:02.071525Z","shell.execute_reply.started":"2022-03-15T13:24:02.065828Z","shell.execute_reply":"2022-03-15T13:24:02.070889Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%%time\n\n# Load all sales data (for 3 years starting from 2018 to 2020)\n# ALso, article_id is treated as a string column otherwise it \n# would drop the leading zeros while reading the specific column values\ntransactions_data=create_data(data_path, data_type='transaction')\nprint(transactions_data.shape)\n\n# # Unique Attributes\nprint(str(len(transactions_data['t_dat'].drop_duplicates())) + \"-total No of unique transactions dates in data sheet\")\nprint(str(len(transactions_data['customer_id'].drop_duplicates())) + \"-total No of unique customers ids in data sheet\")\nprint(str(len(transactions_data['article_id'].drop_duplicates())) + \"-total No of unique article ids courses names in data sheet\")\nprint(str(len(transactions_data['sales_channel_id'].drop_duplicates())) + \"-total No of unique sales channels in data sheet\")","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:24:03.041671Z","iopub.execute_input":"2022-03-15T13:24:03.042117Z","iopub.status.idle":"2022-03-15T13:25:33.107210Z","shell.execute_reply.started":"2022-03-15T13:24:03.042085Z","shell.execute_reply":"2022-03-15T13:25:33.106159Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"transactions_data.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:33.108839Z","iopub.execute_input":"2022-03-15T13:25:33.109080Z","iopub.status.idle":"2022-03-15T13:25:33.129059Z","shell.execute_reply.started":"2022-03-15T13:25:33.109051Z","shell.execute_reply":"2022-03-15T13:25:33.128442Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"transactions_data.info()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:33.130407Z","iopub.execute_input":"2022-03-15T13:25:33.130617Z","iopub.status.idle":"2022-03-15T13:25:33.148620Z","shell.execute_reply.started":"2022-03-15T13:25:33.130590Z","shell.execute_reply":"2022-03-15T13:25:33.147486Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%%time\n\n# Load all Customers\ncustomer_data=create_data(customer_data_path)\nprint(customer_data.shape)\n\nprint(str(len(customer_data['customer_id'].drop_duplicates())) + \"-total No of unique customers ids in customer data sheet\")","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:33.150730Z","iopub.execute_input":"2022-03-15T13:25:33.150999Z","iopub.status.idle":"2022-03-15T13:25:39.199177Z","shell.execute_reply.started":"2022-03-15T13:25:33.150966Z","shell.execute_reply":"2022-03-15T13:25:39.198077Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"customer_data.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:39.200642Z","iopub.execute_input":"2022-03-15T13:25:39.201443Z","iopub.status.idle":"2022-03-15T13:25:39.215967Z","shell.execute_reply.started":"2022-03-15T13:25:39.201406Z","shell.execute_reply":"2022-03-15T13:25:39.215330Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"customer_data.info()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:39.217044Z","iopub.execute_input":"2022-03-15T13:25:39.217541Z","iopub.status.idle":"2022-03-15T13:25:39.850137Z","shell.execute_reply.started":"2022-03-15T13:25:39.217486Z","shell.execute_reply":"2022-03-15T13:25:39.849179Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%%time\n\n# Load all Customers\narticle_data=create_data(article_data_path, data_type='article')\nprint(article_data.shape)\n\nprint(str(len(article_data['article_id'].drop_duplicates())) + \"-total No of unique article ids in article data sheet\")\nprint(str(len(article_data['product_group_name'].drop_duplicates())) + \"-total No of unique product group names in article data sheet\")","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:39.851276Z","iopub.execute_input":"2022-03-15T13:25:39.851525Z","iopub.status.idle":"2022-03-15T13:25:40.987793Z","shell.execute_reply.started":"2022-03-15T13:25:39.851494Z","shell.execute_reply":"2022-03-15T13:25:40.986889Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"article_data.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:40.989218Z","iopub.execute_input":"2022-03-15T13:25:40.989549Z","iopub.status.idle":"2022-03-15T13:25:41.022990Z","shell.execute_reply.started":"2022-03-15T13:25:40.989504Z","shell.execute_reply":"2022-03-15T13:25:41.022105Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"article_data.info()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:41.024157Z","iopub.execute_input":"2022-03-15T13:25:41.024495Z","iopub.status.idle":"2022-03-15T13:25:41.210250Z","shell.execute_reply.started":"2022-03-15T13:25:41.024450Z","shell.execute_reply":"2022-03-15T13:25:41.209363Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Unique Product Group Names\narticle_data['product_group_name'].unique()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:41.212965Z","iopub.execute_input":"2022-03-15T13:25:41.213200Z","iopub.status.idle":"2022-03-15T13:25:41.228437Z","shell.execute_reply.started":"2022-03-15T13:25:41.213172Z","shell.execute_reply":"2022-03-15T13:25:41.227478Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Capturing Seasonal Effect by Limiting the transaction date  \n\nBased on notebook with link: https://www.kaggle.com/tomooinubushi/folk-of-time-is-our-best-friend/notebook","metadata":{}},{"cell_type":"code","source":"transactions_data = transactions_data[transactions_data['t_dat'] > '2020-08-21']\ntransactions_data.shape","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:41.229572Z","iopub.execute_input":"2022-03-15T13:25:41.229835Z","iopub.status.idle":"2022-03-15T13:25:41.415974Z","shell.execute_reply.started":"2022-03-15T13:25:41.229806Z","shell.execute_reply":"2022-03-15T13:25:41.415086Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Aggregating Customers and Articles irrespective of transaction dates","metadata":{}},{"cell_type":"code","source":"transactions_data = transactions_data.groupby(['customer_id','article_id']).agg({'price':'sum','t_dat':'count'}).reset_index()\ntransactions_data = transactions_data[['customer_id','article_id','price']]\ntransactions_data.shape","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:41.417192Z","iopub.execute_input":"2022-03-15T13:25:41.417429Z","iopub.status.idle":"2022-03-15T13:25:43.505600Z","shell.execute_reply.started":"2022-03-15T13:25:41.417401Z","shell.execute_reply":"2022-03-15T13:25:43.504875Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"transactions_data.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:43.506653Z","iopub.execute_input":"2022-03-15T13:25:43.506979Z","iopub.status.idle":"2022-03-15T13:25:43.517781Z","shell.execute_reply.started":"2022-03-15T13:25:43.506951Z","shell.execute_reply":"2022-03-15T13:25:43.516834Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Merging transaction data with articles group name data","metadata":{}},{"cell_type":"code","source":"# Combine article's product group name with transaction's data\nmerged_transactions_data = pd.merge(left=transactions_data, right=article_data[['article_id','product_group_name']], how='left', on='article_id')\nmerged_transactions_data.shape","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:43.519027Z","iopub.execute_input":"2022-03-15T13:25:43.519655Z","iopub.status.idle":"2022-03-15T13:25:43.838006Z","shell.execute_reply.started":"2022-03-15T13:25:43.519617Z","shell.execute_reply":"2022-03-15T13:25:43.837074Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"merged_transactions_data.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:43.839204Z","iopub.execute_input":"2022-03-15T13:25:43.839451Z","iopub.status.idle":"2022-03-15T13:25:43.852005Z","shell.execute_reply.started":"2022-03-15T13:25:43.839422Z","shell.execute_reply":"2022-03-15T13:25:43.850972Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"merged_transactions_data.info()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:43.853369Z","iopub.execute_input":"2022-03-15T13:25:43.853676Z","iopub.status.idle":"2022-03-15T13:25:44.225352Z","shell.execute_reply.started":"2022-03-15T13:25:43.853641Z","shell.execute_reply":"2022-03-15T13:25:44.224385Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Generating user and article index mapping dictionaries","metadata":{}},{"cell_type":"code","source":"def get_customers_list():\n    # Creating a list of users\n    # return np.sort(merged_transactions_data['customer_id'].unique()) TEMP_COMMENT\n    return np.sort(customer_data['customer_id'].unique())\n\ndef get_articles_list():\n    # Creating a list of courses \n    # item_list = merged_transactions_data['article_id'].unique() TEMP_COMMENT\n    item_list = article_data['article_id'].unique()\n    return item_list\n\ndef get_feature_list():\n    # Creating a list of features\n    # feature_list = merged_transactions_data['product_group_name'].unique() TEMP_COMMENT\n    feature_list = article_data['product_group_name'].unique()\n    return feature_list\n\ndef id_mappings(customers_list, articles_list, feature_list):\n    \"\"\"\n    \n    Create id mappings to convert user_id, item_id, and feature_id\n    \n    \"\"\"\n    customer_to_index_mapping = {}\n    index_to_customer_mapping = {}\n    for customer_index, customer_id in enumerate(customers_list):\n        customer_to_index_mapping[customer_id] = customer_index\n        index_to_customer_mapping[customer_index] = customer_id\n        \n    article_to_index_mapping = {}\n    index_to_article_mapping = {}\n    for article_index, article_id in enumerate(articles_list):\n        article_to_index_mapping[article_id] = article_index\n        index_to_article_mapping[article_index] = article_id\n    \n    feature_to_index_mapping = {}\n    index_to_feature_mapping = {}\n    for feature_index, feature_id in enumerate(feature_list):\n        feature_to_index_mapping[feature_id] = feature_index\n        index_to_feature_mapping[feature_index] = feature_id\n        \n    return customer_to_index_mapping, index_to_customer_mapping, \\\n           article_to_index_mapping, index_to_article_mapping, \\\n           feature_to_index_mapping, index_to_feature_mapping","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:44.226827Z","iopub.execute_input":"2022-03-15T13:25:44.227509Z","iopub.status.idle":"2022-03-15T13:25:44.241763Z","shell.execute_reply.started":"2022-03-15T13:25:44.227458Z","shell.execute_reply":"2022-03-15T13:25:44.240397Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Create customer, article and feature lists\ncustomers = get_customers_list()\narticles = get_articles_list()\nfeatures = get_feature_list()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:44.243587Z","iopub.execute_input":"2022-03-15T13:25:44.244216Z","iopub.status.idle":"2022-03-15T13:25:46.344273Z","shell.execute_reply.started":"2022-03-15T13:25:44.244159Z","shell.execute_reply":"2022-03-15T13:25:46.343487Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"customers","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:46.345494Z","iopub.execute_input":"2022-03-15T13:25:46.346408Z","iopub.status.idle":"2022-03-15T13:25:46.352339Z","shell.execute_reply.started":"2022-03-15T13:25:46.346349Z","shell.execute_reply":"2022-03-15T13:25:46.351397Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"articles","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:46.353584Z","iopub.execute_input":"2022-03-15T13:25:46.353907Z","iopub.status.idle":"2022-03-15T13:25:46.366773Z","shell.execute_reply.started":"2022-03-15T13:25:46.353873Z","shell.execute_reply":"2022-03-15T13:25:46.365873Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"features","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:46.368509Z","iopub.execute_input":"2022-03-15T13:25:46.368847Z","iopub.status.idle":"2022-03-15T13:25:46.381307Z","shell.execute_reply.started":"2022-03-15T13:25:46.368807Z","shell.execute_reply":"2022-03-15T13:25:46.380480Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Generate mapping, LightFM library can't read other than (integer) index\ncustomer_to_index_mapping, index_to_customer_mapping, \\\narticle_to_index_mapping, index_to_article_mapping, \\\nfeature_to_index_mapping, index_to_feature_mapping = id_mappings(customers, articles, features)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:46.382644Z","iopub.execute_input":"2022-03-15T13:25:46.383018Z","iopub.status.idle":"2022-03-15T13:25:47.227208Z","shell.execute_reply.started":"2022-03-15T13:25:46.382983Z","shell.execute_reply":"2022-03-15T13:25:47.226203Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Generate Customer Article Interaction Matrix","metadata":{}},{"cell_type":"code","source":"def get_customer_article_interaction(customer_article_amt_df):\n    #start indexing\n    customer_article_amt_df[\"customer_id\"] = customer_article_amt_df[\"customer_id\"]\n    customer_article_amt_df[\"article_id\"] = customer_article_amt_df[\"article_id\"]\n    customer_article_amt_df[\"price\"] = customer_article_amt_df[\"price\"]\n\n    # Preprocessing dataframe created\n    customer_article_amt_df = customer_article_amt_df.rename(columns = {\"price\":\"total_amount_spent\"})\n\n    # Replace Amount Column with category codes \n    customer_article_amt_df['total_amount_spent'] = customer_article_amt_df['total_amount_spent'].astype('category')\n    customer_article_amt_df['total_amount_spent'] = customer_article_amt_df['total_amount_spent'].cat.codes\n\n    return customer_article_amt_df\n\ndef get_interaction_matrix(df, df_column_as_row, df_column_as_col, \n                        df_column_as_value, row_indexing_map, col_indexing_map):\n    \n    row = df[df_column_as_row].apply(lambda x: row_indexing_map[x]).values\n    col = df[df_column_as_col].apply(lambda x: col_indexing_map[x]).values\n    value = df[df_column_as_value].values\n    \n    return sparse.coo_matrix((value, (row, col)), shape = (len(row_indexing_map), len(col_indexing_map)))\n\ndef get_article_feature_interaction(article_product_group_df, product_group_brand_weight = 1):\n    # drop duplicates\n    article_product_group_df = article_product_group_df.drop_duplicates()\n\n    # start indexing\n    article_product_group_df[\"article_id\"] = article_product_group_df[\"article_id\"]\n    article_product_group_df[\"product_group_name\"] = article_product_group_df[\"product_group_name\"]\n\n    # allocate \"product_group_name\" into one column as \"feature\"\n    article_product_group_df = article_product_group_df[[\"article_id\", \"product_group_name\"]].rename(columns = {\"product_group_name\" : \"feature_01\"})\n    article_product_group_df[\"feature_count\"] = product_group_brand_weight # adding weight to feature\n        \n    # grouping for summing over feature_count\n    article_product_group_df = article_product_group_df.groupby([\"article_id\", \"feature_01\"], as_index = False)[\"feature_count\"].sum()\n    \n    return article_product_group_df\n","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:47.228848Z","iopub.execute_input":"2022-03-15T13:25:47.229382Z","iopub.status.idle":"2022-03-15T13:25:47.240777Z","shell.execute_reply.started":"2022-03-15T13:25:47.229332Z","shell.execute_reply":"2022-03-15T13:25:47.239839Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Create customer and article interaction dataframe\ncustomer_to_article = get_customer_article_interaction(customer_article_amt_df = merged_transactions_data[['customer_id','article_id','price']])\n\n# Create article and feature interaction dataframe\narticle_to_feature = get_article_feature_interaction(article_product_group_df = merged_transactions_data[['article_id','product_group_name']], \n                                                    product_group_brand_weight = 1)\n\nprint(customer_to_article.shape)   \nprint(article_to_feature.shape)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:47.241953Z","iopub.execute_input":"2022-03-15T13:25:47.242185Z","iopub.status.idle":"2022-03-15T13:25:47.784645Z","shell.execute_reply.started":"2022-03-15T13:25:47.242155Z","shell.execute_reply":"2022-03-15T13:25:47.783780Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"customer_to_article.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:47.785875Z","iopub.execute_input":"2022-03-15T13:25:47.786105Z","iopub.status.idle":"2022-03-15T13:25:47.797936Z","shell.execute_reply.started":"2022-03-15T13:25:47.786075Z","shell.execute_reply":"2022-03-15T13:25:47.796753Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"article_to_feature.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:47.799468Z","iopub.execute_input":"2022-03-15T13:25:47.799813Z","iopub.status.idle":"2022-03-15T13:25:47.816215Z","shell.execute_reply.started":"2022-03-15T13:25:47.799765Z","shell.execute_reply":"2022-03-15T13:25:47.815519Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Generate customer_article_interaction_matrix for train data\ncustomer_to_article_interaction = get_interaction_matrix(customer_to_article, \"customer_id\", \"article_id\", \"total_amount_spent\", \\\n                                                    customer_to_index_mapping, article_to_index_mapping)\n\n# Generate article_to_feature interaction\narticle_to_feature_interaction = get_interaction_matrix(article_to_feature, \"article_id\", \"feature_01\",  \"feature_count\", \\\n                                                       article_to_index_mapping, feature_to_index_mapping)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:47.817753Z","iopub.execute_input":"2022-03-15T13:25:47.818084Z","iopub.status.idle":"2022-03-15T13:25:49.443252Z","shell.execute_reply.started":"2022-03-15T13:25:47.818026Z","shell.execute_reply":"2022-03-15T13:25:49.442629Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"customer_to_article_interaction","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:49.449178Z","iopub.execute_input":"2022-03-15T13:25:49.449732Z","iopub.status.idle":"2022-03-15T13:25:49.456533Z","shell.execute_reply.started":"2022-03-15T13:25:49.449679Z","shell.execute_reply":"2022-03-15T13:25:49.455571Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"article_to_feature_interaction","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:49.457781Z","iopub.execute_input":"2022-03-15T13:25:49.458084Z","iopub.status.idle":"2022-03-15T13:25:49.472009Z","shell.execute_reply.started":"2022-03-15T13:25:49.458041Z","shell.execute_reply":"2022-03-15T13:25:49.471018Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Light FM Model Training","metadata":{}},{"cell_type":"code","source":"#### FULL MODEL TRAINING ####\n# Retraining the final model with full dataset\n\"\"\"\nTraining model without any article or customer features\n\"\"\"\nfinal_model_without_feature = LightFM(loss = \"warp\")\n\n# Fitting to combined dataset with pure collaborative filtering result\nstart = time.time() \nfinal_model_without_feature.fit(customer_to_article_interaction,\n                                user_features=None, \n                                item_features=None, \n                                sample_weight=None, \n                                epochs=1, \n                                num_threads=4, \n                                verbose=False)\nend = time.time()\nprint(\"time taken = {0:.{1}f} seconds\".format(end - start, 2))\n\n\"\"\"\nTraining model with article feature (article's product_group_name)\n\"\"\"\nfinal_model_with_1_feature = LightFM(loss = \"warp\")\n\n# Fitting to combined dataset with pure collaborative filtering result\nstart = time.time() \nfinal_model_with_1_feature.fit(customer_to_article_interaction,\n                            user_features=None, \n                            item_features=article_to_feature_interaction, \n                            sample_weight=None, \n                            epochs=1, \n                            num_threads=4, \n                            verbose=False)\nend = time.time()\nprint(\"time taken = {0:.{1}f} seconds\".format(end - start, 2))","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:49.473533Z","iopub.execute_input":"2022-03-15T13:25:49.474673Z","iopub.status.idle":"2022-03-15T13:25:51.673250Z","shell.execute_reply.started":"2022-03-15T13:25:49.474624Z","shell.execute_reply":"2022-03-15T13:25:51.672359Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Recommendation sampling and Comparison with Known Positives","metadata":{}},{"cell_type":"code","source":"class recommendation_sampling():\n    def __init__(self, model, items = None, user_to_product_interaction_matrix = None, \n                item_features = None, user2index_map = None):\n        \n        self.user_to_product_interaction_matrix = user_to_product_interaction_matrix\n        self.item_features = item_features if item_features is not None else None\n        self.model = model\n        self.items = items\n        self.user2index_map = user2index_map\n    \n    def recommendation_for_user(self, user, k=3, prediction_type = 'normal'):\n        # Getting the userindex\n        userindex = self.user2index_map.get(user, None)\n        if userindex == None:\n            print(\"User %s not provided during Training the model\" %(user))\n            return None\n        \n        # Products already bought\n        known_positives = self.items[self.user_to_product_interaction_matrix.tocsr()[userindex].indices]\n        \n        # Scores from model prediction\n        scores = self.model.predict(user_ids = userindex, item_ids = np.arange(self.user_to_product_interaction_matrix.shape[1])) if prediction_type == 'normal' else \\\n            self.model.predict(user_ids = userindex, item_ids = np.arange(self.user_to_product_interaction_matrix.shape[1]), item_features = self.item_features)\n    \n        # Top items\n        top_items = self.items[np.argsort(-scores)]\n        \n        # Printing out the result\n        print(\"User %s\" % user)\n        print(\"     Known positives:\")\n        for x in known_positives[:k]:\n            print(\"                  %s\" % x)\n            \n        print(\"     Recommended:\")\n        for x in top_items[:k]:\n            print(\"                  %s\" % x)\n\n    def get_recommendation(self, user, k=3, prediction_type = 'normal'):\n        # Getting the userindex\n        userindex = self.user2index_map.get(user, None)\n        if userindex == None:\n            return None\n        \n        # Products already bought\n        known_positives = self.items[self.user_to_product_interaction_matrix.tocsr()[userindex].indices]\n        \n        # Scores from model prediction\n        scores = self.model.predict(user_ids = userindex, item_ids = np.arange(self.user_to_product_interaction_matrix.shape[1])) if prediction_type == 'normal' else \\\n            self.model.predict(user_ids = userindex, item_ids = np.arange(self.user_to_product_interaction_matrix.shape[1]), item_features = self.item_features)\n        \n        # Top items\n        top_items = self.items[np.argsort(-scores)]\n\n        # Returning results\n        recommended_list, recommender_count = [],1\n        for item in top_items[:k]:\n            recommended_list.append({'Priority': recommender_count,'Article': item})\n            recommender_count+=1\n        return known_positives, recommended_list\n    \n    def get_batched_recommendation(self, user, k=3, prediction_type='normal'):\n        # Getting user_indexes \n        user_index = self.user2index_map.get(user, None)\n        if user_index is None:\n            return None\n        \n        # Scores from model\n        scores = self.model.predict(user_ids = user_index, item_ids = np.arange(self.user_to_product_interaction_matrix.shape[1])) if prediction_type == 'normal' else \\\n            self.model.predict(user_ids = user_index, item_ids = np.arange(self.user_to_product_interaction_matrix.shape[1]), item_features = self.item_features)\n    \n        # Top items\n        top_items = self.items[np.argsort(-scores)]\n        \n        return top_items[:k]","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:51.674870Z","iopub.execute_input":"2022-03-15T13:25:51.675153Z","iopub.status.idle":"2022-03-15T13:25:51.697285Z","shell.execute_reply.started":"2022-03-15T13:25:51.675115Z","shell.execute_reply":"2022-03-15T13:25:51.696294Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Giving recommendations\nrecom_without_feature = recommendation_sampling(model = final_model_without_feature,\n                                               items = articles,\n                                               user_to_product_interaction_matrix = customer_to_article_interaction,\n                                               user2index_map = customer_to_index_mapping)\n\nrecom_with_1_feature = recommendation_sampling(model = final_model_with_1_feature,\n                                               items = articles,\n                                               user_to_product_interaction_matrix = customer_to_article_interaction,\n                                               item_features = article_to_feature_interaction,\n                                               user2index_map = customer_to_index_mapping)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:51.698956Z","iopub.execute_input":"2022-03-15T13:25:51.699286Z","iopub.status.idle":"2022-03-15T13:25:51.719904Z","shell.execute_reply.started":"2022-03-15T13:25:51.699241Z","shell.execute_reply":"2022-03-15T13:25:51.718934Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"recom_without_feature.recommendation_for_user('00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d25f88aa139fdfc657')\nrecom_without_feature.recommendation_for_user('0000423b00ade91418cceaf3b26c6af3dd342b51fd051eec9c12fb36984420fa')\nrecom_without_feature.recommendation_for_user('000058a12d5b43e67d225668fa1f8d618c13dc232df0cad8ffe7ad4a1091e318')\nrecom_without_feature.recommendation_for_user('00005ca1c9ed5f5146b52ac8639a40ca9d57aeff4d1bd2c5feb1ca5dff07c43e')\nrecom_without_feature.recommendation_for_user('00006413d8573cd20ed7128e53b7b13819fe5cfc2d801fe7fc0f26dd8d65a85a')","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:51.721624Z","iopub.execute_input":"2022-03-15T13:25:51.721938Z","iopub.status.idle":"2022-03-15T13:25:51.938593Z","shell.execute_reply.started":"2022-03-15T13:25:51.721895Z","shell.execute_reply":"2022-03-15T13:25:51.937451Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"recom_with_1_feature.recommendation_for_user(user = '00000dbacae5abe5e23885899a1fa44253a17956c6d1c3d25f88aa139fdfc657', prediction_type = 'feature')\nrecom_with_1_feature.recommendation_for_user(user = '0000423b00ade91418cceaf3b26c6af3dd342b51fd051eec9c12fb36984420fa', prediction_type = 'feature')\nrecom_with_1_feature.recommendation_for_user(user = '000058a12d5b43e67d225668fa1f8d618c13dc232df0cad8ffe7ad4a1091e318', prediction_type = 'feature')\nrecom_with_1_feature.recommendation_for_user(user = '00005ca1c9ed5f5146b52ac8639a40ca9d57aeff4d1bd2c5feb1ca5dff07c43e', prediction_type = 'feature')\nrecom_with_1_feature.recommendation_for_user(user = '00006413d8573cd20ed7128e53b7b13819fe5cfc2d801fe7fc0f26dd8d65a85a', prediction_type = 'feature')","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:51.939794Z","iopub.execute_input":"2022-03-15T13:25:51.940005Z","iopub.status.idle":"2022-03-15T13:25:52.090110Z","shell.execute_reply.started":"2022-03-15T13:25:51.939979Z","shell.execute_reply":"2022-03-15T13:25:52.089015Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## MAP@12 Calculation for entire dataset","metadata":{}},{"cell_type":"code","source":"sparse_customer_article_train, sparse_customer_article_test = random_train_test_split(customer_to_article_interaction, test_percentage=0.2, random_state=42)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:52.091341Z","iopub.execute_input":"2022-03-15T13:25:52.091666Z","iopub.status.idle":"2022-03-15T13:25:52.161362Z","shell.execute_reply.started":"2022-03-15T13:25:52.091629Z","shell.execute_reply":"2022-03-15T13:25:52.160410Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sparse_customer_article_train","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:52.162738Z","iopub.execute_input":"2022-03-15T13:25:52.163058Z","iopub.status.idle":"2022-03-15T13:25:52.170095Z","shell.execute_reply.started":"2022-03-15T13:25:52.163018Z","shell.execute_reply":"2022-03-15T13:25:52.168927Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sparse_customer_article_test","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:52.171752Z","iopub.execute_input":"2022-03-15T13:25:52.172060Z","iopub.status.idle":"2022-03-15T13:25:52.183236Z","shell.execute_reply.started":"2022-03-15T13:25:52.172018Z","shell.execute_reply":"2022-03-15T13:25:52.182389Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Cross Validation methodolody","metadata":{}},{"cell_type":"code","source":"# Initialising model with warp loss function\nmodel_with_1_feature = LightFM(loss = \"warp\")\n\n# Fitting into user to product interaction matrix only / pure collaborative filtering factor\nstart = time.time()\nmodel_with_1_feature.fit(sparse_customer_article_train,\n                      user_features=None, \n                      item_features=article_to_feature_interaction, \n                      sample_weight=None, \n                      epochs=1, \n                      num_threads=4,\n                      verbose=False)\nend = time.time()\nprint(\"time taken = {0:.{1}f} seconds\".format(end - start, 2))","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:52.184390Z","iopub.execute_input":"2022-03-15T13:25:52.184682Z","iopub.status.idle":"2022-03-15T13:25:53.209525Z","shell.execute_reply.started":"2022-03-15T13:25:52.184640Z","shell.execute_reply":"2022-03-15T13:25:53.208532Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Writing Precision Calculation","metadata":{}},{"cell_type":"code","source":"# Precision metric score (ranging from 0 to 1)\n'''\nk = 12\nprecision_with_1_article_feature = []\nfor precision_k in tqdm.tqdm(range(1,k+1), desc='Calculating Precisions at different k levels with 1 article feature'):\n    start = time.time()\n    precision_value = precision_at_k(model = model_with_1_feature, \n                                    test_interactions = sparse_customer_article_test,\n                                    item_features = article_to_feature_interaction,\n                                    num_threads = 4, \n                                    k=precision_k,\n                                    check_intersections = False)\n    print('Average Precision@k value for top %s numbered precision = %s' %(str(precision_k), str(precision_value.mean())))\n    precision_with_1_article_feature.append(precision_value)\n    end = time.time()\n    print(\"Time taken for top %s number precision = %s seconds\" %(str(precision_k), str(round(end-start,2))))\n'''","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:53.211017Z","iopub.execute_input":"2022-03-15T13:25:53.211374Z","iopub.status.idle":"2022-03-15T13:25:53.219155Z","shell.execute_reply.started":"2022-03-15T13:25:53.211327Z","shell.execute_reply":"2022-03-15T13:25:53.218382Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Screenshot of precision calculation\n![image.png](attachment:8303c16b-1206-4653-9ea7-5c9fa5143b6a.png)","metadata":{},"attachments":{"8303c16b-1206-4653-9ea7-5c9fa5143b6a.png":{"image/png":"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"}}},{"cell_type":"code","source":"'''\nfrom numpy import save\nsave('./precision_with_1_article_feature_reduced.npy', precision_with_1_article_feature)\n'''","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:53.220533Z","iopub.execute_input":"2022-03-15T13:25:53.220780Z","iopub.status.idle":"2022-03-15T13:25:53.240415Z","shell.execute_reply.started":"2022-03-15T13:25:53.220745Z","shell.execute_reply":"2022-03-15T13:25:53.239670Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"precision_with_1_article_feature = np.load('../input/hm-trained-models/lightfm_1articlefeature/precision_with_1_article_feature_reduced.npy')","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:53.241636Z","iopub.execute_input":"2022-03-15T13:25:53.242264Z","iopub.status.idle":"2022-03-15T13:25:53.282687Z","shell.execute_reply.started":"2022-03-15T13:25:53.242225Z","shell.execute_reply":"2022-03-15T13:25:53.281897Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Calculating Average Precision@12","metadata":{}},{"cell_type":"code","source":"map_12 = np.sum(precision_with_1_article_feature, axis=0) / 12","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:53.284255Z","iopub.execute_input":"2022-03-15T13:25:53.284935Z","iopub.status.idle":"2022-03-15T13:25:53.290173Z","shell.execute_reply.started":"2022-03-15T13:25:53.284893Z","shell.execute_reply":"2022-03-15T13:25:53.289117Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Calculating Mean Average Precision","metadata":{}},{"cell_type":"code","source":"print(\"average precision @ 12 by adding 1 article-feature interaction = {0:.{1}f}\".format(map_12.mean(), 3)) ","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:53.291724Z","iopub.execute_input":"2022-03-15T13:25:53.292225Z","iopub.status.idle":"2022-03-15T13:25:53.305756Z","shell.execute_reply.started":"2022-03-15T13:25:53.292179Z","shell.execute_reply":"2022-03-15T13:25:53.304826Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Saving Final Model with any feature","metadata":{}},{"cell_type":"code","source":"with open('model_with_1_article_feature_reduced.pickle', 'wb') as fle:\n    pickle.dump(final_model_with_1_feature, fle, protocol=pickle.HIGHEST_PROTOCOL)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:53.307575Z","iopub.execute_input":"2022-03-15T13:25:53.307862Z","iopub.status.idle":"2022-03-15T13:25:53.664443Z","shell.execute_reply.started":"2022-03-15T13:25:53.307823Z","shell.execute_reply":"2022-03-15T13:25:53.663385Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Getting Predictions based on submission template","metadata":{}},{"cell_type":"code","source":"submission_data = pd.read_csv(submission_data_path)\nsubmission_data.shape","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:53.665792Z","iopub.execute_input":"2022-03-15T13:25:53.666035Z","iopub.status.idle":"2022-03-15T13:25:58.635271Z","shell.execute_reply.started":"2022-03-15T13:25:53.666004Z","shell.execute_reply":"2022-03-15T13:25:58.634299Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission_data.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:58.636360Z","iopub.execute_input":"2022-03-15T13:25:58.636572Z","iopub.status.idle":"2022-03-15T13:25:58.648825Z","shell.execute_reply.started":"2022-03-15T13:25:58.636546Z","shell.execute_reply":"2022-03-15T13:25:58.647792Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"submission_data.loc[submission_data.customer_id.isin([submission_data.customer_id.unique()[0]])].prediction[0].split(' ')","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:58.650424Z","iopub.execute_input":"2022-03-15T13:25:58.650843Z","iopub.status.idle":"2022-03-15T13:25:59.337651Z","shell.execute_reply.started":"2022-03-15T13:25:58.650796Z","shell.execute_reply":"2022-03-15T13:25:59.336635Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def create_chunk_indices(meta_df, chunk_idx, chunk_size):\n    '''\n    Function to generate chunks of data for multiprocessing\n    '''\n    start_idx = chunk_idx * chunk_size\n    end_idx = start_idx + chunk_size\n    meta_chunk = meta_df[start_idx:end_idx]\n    print(\"start/end \"+str(chunk_idx+1)+\":\" + str(start_idx) + \",\" + str(end_idx))\n    print(len(meta_chunk))\n    #chunk_idx in return value is used to sort the processed chunks back into original order,\n    return (meta_chunk, chunk_idx)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:59.339928Z","iopub.execute_input":"2022-03-15T13:25:59.340180Z","iopub.status.idle":"2022-03-15T13:25:59.347176Z","shell.execute_reply.started":"2022-03-15T13:25:59.340139Z","shell.execute_reply":"2022-03-15T13:25:59.346196Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def predict_sub_chunks(chunk):\n    final_submission=[]\n    for row in tqdm.tqdm(chunk[0].values):\n        try:\n            preds = recom_with_1_feature.get_batched_recommendation(user = row[0], k = 12, prediction_type = 'feature')\n            if preds is not None:\n                final_submission.append(' '.join(map(str, preds)))\n            else:\n                final_submission.append(row[1])\n        except Exception as ex:\n            print(ex)\n    return final_submission","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:59.348539Z","iopub.execute_input":"2022-03-15T13:25:59.348765Z","iopub.status.idle":"2022-03-15T13:25:59.366133Z","shell.execute_reply.started":"2022-03-15T13:25:59.348737Z","shell.execute_reply":"2022-03-15T13:25:59.365343Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"num_cores=4\n\ndef predict_submission(submission_data=None):\n    #splitting here by measurement id's to get all signals for a measurement into single chunk\n    customer_ids = submission_data[\"customer_id\"].unique()\n    df_split = np.array_split(customer_ids, num_cores)\n    chunk_size = len(df_split[0])\n    \n    chunk1 = create_chunk_indices(submission_data, 0, chunk_size)\n    chunk2 = create_chunk_indices(submission_data, 1, chunk_size)\n    chunk3 = create_chunk_indices(submission_data, 2, chunk_size)\n    chunk4 = create_chunk_indices(submission_data, 3, chunk_size)\n    \n    #list of items for multiprocessing, 4 since using 4 cores\n    all_chunks = [chunk1, chunk2, chunk3, chunk4]\n    \n    pool = Pool(num_cores)\n    result = pool.map(predict_sub_chunks, all_chunks)\n    \n    result_combined = list(itertools.chain(result[0], result[1], result[2], result[3]))\n    return result_combined","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:59.367447Z","iopub.execute_input":"2022-03-15T13:25:59.367728Z","iopub.status.idle":"2022-03-15T13:25:59.380178Z","shell.execute_reply.started":"2022-03-15T13:25:59.367689Z","shell.execute_reply":"2022-03-15T13:25:59.379414Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### The inferencing is done for first 1024 users in the sample file however you can find the complete prediction file in the dataset:  \nLightFM dataset link: https://www.kaggle.com/rickykonwar/hm-trained-models","metadata":{}},{"cell_type":"code","source":"final_predictions = predict_submission(submission_data[:1024])","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:25:59.381478Z","iopub.execute_input":"2022-03-15T13:25:59.381736Z","iopub.status.idle":"2022-03-15T13:26:05.220581Z","shell.execute_reply.started":"2022-03-15T13:25:59.381698Z","shell.execute_reply":"2022-03-15T13:26:05.219243Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Screenshot of Inferencing entire sample submission data\n\n![image.png](attachment:f2101c17-b4fb-43ba-99c2-2081711ee834.png)","metadata":{},"attachments":{"f2101c17-b4fb-43ba-99c2-2081711ee834.png":{"image/png":"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"}}},{"cell_type":"code","source":"len(final_predictions)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:26:05.223050Z","iopub.execute_input":"2022-03-15T13:26:05.223426Z","iopub.status.idle":"2022-03-15T13:26:05.232616Z","shell.execute_reply.started":"2022-03-15T13:26:05.223387Z","shell.execute_reply":"2022-03-15T13:26:05.231882Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Writing Intermediate Predictions","metadata":{}},{"cell_type":"code","source":"final_submission_data = submission_data.copy()[:1024]\nfinal_submission_data['prediction'] = final_predictions","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:26:05.233865Z","iopub.execute_input":"2022-03-15T13:26:05.234809Z","iopub.status.idle":"2022-03-15T13:26:05.506123Z","shell.execute_reply.started":"2022-03-15T13:26:05.234769Z","shell.execute_reply":"2022-03-15T13:26:05.505262Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"final_submission_data.head()","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:26:05.507601Z","iopub.execute_input":"2022-03-15T13:26:05.507868Z","iopub.status.idle":"2022-03-15T13:26:05.519528Z","shell.execute_reply.started":"2022-03-15T13:26:05.507837Z","shell.execute_reply":"2022-03-15T13:26:05.518585Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"final_submission_data.to_csv(\"intermediate_submission.csv\", index=False)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:26:05.521042Z","iopub.execute_input":"2022-03-15T13:26:05.521770Z","iopub.status.idle":"2022-03-15T13:26:05.544272Z","shell.execute_reply.started":"2022-03-15T13:26:05.521719Z","shell.execute_reply":"2022-03-15T13:26:05.543562Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from IPython.display import FileLink\nFileLink(r'intermediate_submission.csv')","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:26:05.545771Z","iopub.execute_input":"2022-03-15T13:26:05.546408Z","iopub.status.idle":"2022-03-15T13:26:05.553631Z","shell.execute_reply.started":"2022-03-15T13:26:05.546360Z","shell.execute_reply":"2022-03-15T13:26:05.552716Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Writing Complete Predictions","metadata":{}},{"cell_type":"code","source":"actual_submission_data = pd.read_csv(r'../input/hm-trained-models/lightfm_1articlefeature/submission_reduced.csv')\nactual_submission_data.to_csv(\"submission.csv\", index=False)","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:26:05.555717Z","iopub.execute_input":"2022-03-15T13:26:05.556339Z","iopub.status.idle":"2022-03-15T13:26:23.610305Z","shell.execute_reply.started":"2022-03-15T13:26:05.556270Z","shell.execute_reply":"2022-03-15T13:26:23.609420Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from IPython.display import FileLink\nFileLink(r'submission.csv')","metadata":{"execution":{"iopub.status.busy":"2022-03-15T13:26:23.611731Z","iopub.execute_input":"2022-03-15T13:26:23.612175Z","iopub.status.idle":"2022-03-15T13:26:23.617956Z","shell.execute_reply.started":"2022-03-15T13:26:23.612142Z","shell.execute_reply":"2022-03-15T13:26:23.617387Z"},"trusted":true},"execution_count":null,"outputs":[]}]}