{"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":"# XGBoost Baseline - LB 0.678 - 05.12\n이 노트북에서는 XGBoost 기준선을 제시합니다. 18개의 질문 각각에 대해 GroupKFold 모델을 훈련합니다. CV 점수는 0.678점입니다. KFold 모델 중 하나를 사용하여 테스트를 추론합니다. xgboost에 더 많은 기능을 엔지니어링하거나 다른 모델(예: 다른 ML 모델 및/또는 RNN 및/또는 Transformer)을 시도하여 CV와 LB를 개선할 수 있습니다. 또한 더 많은 KFold 모델을 사용하거나 모든 데이터(및 KFold 교차 검증에서 찾은 하이퍼파라미터)를 사용하여 하나의 모델을 학습시킴으로써 LB를 개선할 수 있습니다.\n\n**업데이트** 2023년 3월 20일, Kaggle은 훈련 데이터의 크기를 두 배로 늘렸습니다. 따라서 메모리 오류를 피하기 위해 이 노트북을 업데이트했습니다. 이를 위해 열차 데이터를 청크 단위로 읽고 피처 엔지니어링을 청크 단위로 수행합니다. 메모리 오류를 방지하는 또 다른 방법은 두 개의 노트북을 사용하는 것입니다. 32GB RAM이 있는 하나의 노트북에서 모델을 훈련하고 모델을 저장한 다음, 필요한 8GB RAM 노트북(로드된 모델 포함)을 두 번째 노트북으로 제출합니다. (토론 [여기][1] 참조\n\n[1]: https://www.kaggle.com/competitions/predict-student-performance-from-game-play/discussion/386218\n\nKFold교차 검증이란? \n가장 보편적으로 사용되는 교차 검증 기법\n먼저 K개의 데이터 폴드 세트를 만들어서 K번만큼 각 폴드 세트에 학습과 검증 평가를 반복적으로 수행하는 방법\n즉, Training data랑 Test data를 적절히 섞어서 여러 결과를 내 교차검증 하는 것","metadata":{"papermill":{"duration":0.005932,"end_time":"2023-02-07T00:59:58.147501","exception":false,"start_time":"2023-02-07T00:59:58.141569","status":"completed"},"tags":[]}},{"cell_type":"code","source":"import pandas as pd, numpy as np, gc\nfrom sklearn.model_selection import KFold, GroupKFold\nfrom xgboost import XGBClassifier\nfrom sklearn.metrics import f1_score","metadata":{"papermill":{"duration":1.027875,"end_time":"2023-02-07T00:59:59.180261","exception":false,"start_time":"2023-02-07T00:59:58.152386","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:35:20.533547Z","iopub.execute_input":"2023-07-25T05:35:20.534057Z","iopub.status.idle":"2023-07-25T05:35:20.540490Z","shell.execute_reply.started":"2023-07-25T05:35:20.534018Z","shell.execute_reply":"2023-07-25T05:35:20.539291Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# 훈련 데이터 및 레이블 로드\n2023년 3월 20일, Kaggle은 훈련 데이터의 크기를 두 배로 늘렸습니다(토론 [여기][1] 참조). 이제 열차 데이터는 4.7GB입니다! 메모리 오류를 피하기 위해 열차 데이터를 10개의 조각으로 읽고 다음 조각을 읽기 전에 각 조각을 피처 엔지니어링할 것입니다. 피처 엔지니어링은 각 조각의 크기를 줄이기 때문에 이 방법이 효과적입니다.\n\n[1]: https://www.kaggle.com/competitions/predict-student-performance-from-game-play/discussion/396202","metadata":{"papermill":{"duration":0.004542,"end_time":"2023-02-07T00:59:59.189777","exception":false,"start_time":"2023-02-07T00:59:59.185235","status":"completed"},"tags":[]}},{"cell_type":"code","source":"#train을 쪼갤 크기 구하기\n\n# READ USER ID ONLY\ntmp = pd.read_csv(\"/kaggle/input/predict-student-performance-from-game-play/train.csv\",usecols=[0])\n#동일한 session_id가 몇개 있는지 확인\ntmp = tmp.groupby('session_id').session_id.agg('count')\n\n# COMPUTE READS AND SKIPS\nPIECES = 10\n#데이터를 10개의 그룹으로 나누고 그룹별 크기를 올림 계산해서 CHUNK에 저장(즉, CHUNK가 각 그룹의 크기). 메모리로 인한 오류를 방지하기 위함\nCHUNK = int( np.ceil(len(tmp)/PIECES) )\n\nreads = [] # 그룹별 session_id 의 개수를 저장 할 공간\nskips = [0] # session_id가 이어지는 구간을 저장 할 공간\nfor k in range(PIECES): #그룹의 수(10개) 만큼 반복\n    a = k*CHUNK # n*CHUNK ~ (n+1)*CHUNK 번째를 계산하기 위한 구간1\n    b = (k+1)*CHUNK # 구간2\n    if b>len(tmp): b=len(tmp) # 끝나는 번호가 총 길이보다 커졌다면, 끝나는 번호를 총 길이로 수정해준다\n    r = tmp.iloc[a:b].sum() # 구간 a~b 인덱스에 위치한 id컬럼(동일한 세션id의 개수) 값들의 합을 구한다\n    reads.append(r) # n번째 구간을 reades 리스트의 n번째에 추가한다\n    skips.append(skips[-1]+r) # 이때까지 구한 session_id의 개수를 추가한다 \n    \nprint(f'To avoid memory error, we will read train in {PIECES} pieces of sizes:')\nprint(reads)\nprint(skips)","metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2023-07-25T05:35:21.447502Z","iopub.execute_input":"2023-07-25T05:35:21.448634Z","iopub.status.idle":"2023-07-25T05:36:35.382191Z","shell.execute_reply.started":"2023-07-25T05:35:21.448582Z","shell.execute_reply":"2023-07-25T05:36:35.380810Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#train data 가져오기\n\ntrain = pd.read_csv('/kaggle/input/predict-student-performance-from-game-play/train.csv', nrows=reads[0])\nprint('Train size of first piece:', train.shape )\ntrain.head(20)","metadata":{"papermill":{"duration":59.284316,"end_time":"2023-02-07T01:00:58.478743","exception":false,"start_time":"2023-02-07T00:59:59.194427","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:36:35.384497Z","iopub.execute_input":"2023-07-25T05:36:35.384871Z","iopub.status.idle":"2023-07-25T05:36:45.075502Z","shell.execute_reply.started":"2023-07-25T05:36:35.384839Z","shell.execute_reply":"2023-07-25T05:36:45.074314Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"#정답 파일(train_labels)을 가져옴\ntargets = pd.read_csv('/kaggle/input/predict-student-performance-from-game-play/train_labels.csv')\n#session_id에 있는 _를 기준으로 session과 question number를 나눈다\ntargets['session'] = targets.session_id.apply(lambda x: int(x.split('_')[0]) )\ntargets['q'] = targets.session_id.apply(lambda x: int(x.split('_')[-1][1:]) )\nprint( targets.shape )\ntargets.head()","metadata":{"papermill":{"duration":0.598155,"end_time":"2023-02-07T01:00:59.082015","exception":false,"start_time":"2023-02-07T01:00:58.48386","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:36:45.077486Z","iopub.execute_input":"2023-07-25T05:36:45.078516Z","iopub.status.idle":"2023-07-25T05:36:46.637045Z","shell.execute_reply.started":"2023-07-25T05:36:45.078474Z","shell.execute_reply":"2023-07-25T05:36:46.636058Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Feature Engineer\n저희는 기본적인 집계 기능을 만듭니다. 더 많은 기능을 만들어 CV와 LB를 향상시켜 보세요! 이벤트 기능에 대한 아이디어는 [여기][1]에서 가져왔습니다.\n\n[1]: https://www.kaggle.com/code/kimtaehun/lightgbm-baseline-with-aggregated-log-data","metadata":{"papermill":{"duration":0.005196,"end_time":"2023-02-07T01:00:59.092865","exception":false,"start_time":"2023-02-07T01:00:59.087669","status":"completed"},"tags":[]}},{"cell_type":"code","source":"#범주형 데이터와 수치형 데이터를 구분한다\nCATS = ['event_name', 'fqid', 'room_fqid', 'text'] #범주형 데이터\nNUMS = ['elapsed_time','level','page','room_coor_x', 'room_coor_y', \n        'screen_coor_x', 'screen_coor_y', 'hover_duration'] #수치형 데이터\n\n# https://www.kaggle.com/code/kimtaehun/lightgbm-baseline-with-aggregated-log-data\n#이벤트를 구분한다\nEVENTS = ['navigate_click','person_click','cutscene_click','object_click',\n          'map_hover','notification_click','map_click','observation_click',\n          'checkpoint']","metadata":{"papermill":{"duration":0.014685,"end_time":"2023-02-07T01:00:59.112856","exception":false,"start_time":"2023-02-07T01:00:59.098171","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:36:46.638596Z","iopub.execute_input":"2023-07-25T05:36:46.639265Z","iopub.status.idle":"2023-07-25T05:36:46.645832Z","shell.execute_reply.started":"2023-07-25T05:36:46.639230Z","shell.execute_reply":"2023-07-25T05:36:46.644675Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# train data를 기반으로 세션별 feature engineering을 수행하여 새로운 데이터 프레임 생성\n# 각 세션의 고유 식별자인 session_id로 그룹화하여 범주형 데이터에서 고유값 수, 수치형 데이터에서 평균,표준편자를 구하고\n# 이벤트와 경과 시간 데이터에서 합을 구하고, 결과값을 새로운 데아터 프레임으로 반환한다\n# 이벤트 데이터는 아래의 astype('int8')을 통해 이진 플래그로 변환, 변환된 데이터는 이후에 데이터프레임에서 제거된다\ndef feature_engineer(train):\n    dfs = [] # depth first search\n    #train 데이터에서 session_id, level_group으로 그룹화하여\n    for c in CATS:\n        #범주형 데이터들에 대한 nunique(고유값)를 구해 tmp에 저장, 이름 변경 후 dfs에 추가(즉, 값 종류와 그값의 개수)\n        tmp = train.groupby(['session_id','level_group'])[c].agg('nunique') #session_id와 level_group에 따라 c의 고유값을 구해 그룹화해라\n        tmp.name = tmp.name + '_nunique'\n        dfs.append(tmp)\n    for c in NUMS: \n        #수치형 데이터들에 대한 mean(평균)을 구해 tmp에 저장, 이름 변경 후 dfs에 추가\n        tmp = train.groupby(['session_id','level_group'])[c].agg('mean') #session_id와 level_group에 따라 c의 평균값을 구해 그룹화해라\n        tmp.name = tmp.name + '_mean'\n        dfs.append(tmp)\n    for c in NUMS:\n        #수치형 데이터들에 대한 std(표준편차)을 구해 tmp에 저장, 이름 변경 후 dfs에 추가\n        tmp = train.groupby(['session_id','level_group'])[c].agg('std') #session_id와 level_group에 따라 c의 표준편차를 구해 그룹화해라\n        tmp.name = tmp.name + '_std'\n        dfs.append(tmp)\n    for c in EVENTS: \n        #train 데이터의 event_name == 클릭이벤트 인 곳의 타입을 int8,즉 이진 플래그 1, 아닌곳을 0으로 변경\n        train[c] = (train.event_name == c).astype('int8') #astype : 캐스팅\n    for c in EVENTS + ['elapsed_time']:\n        #클릭이벤트 + ['elapsed_time'] 의 sum(합)을 저장, 이름 변경 후 dfs에 추가\n        #즉, 클릭 이벤트의 개수(몇번 클릭했는지)를 구함\n        tmp = train.groupby(['session_id','level_group'])[c].agg('sum')\n        tmp.name = tmp.name + '_sum'\n        dfs.append(tmp)\n    train = train.drop(EVENTS,axis=1)\n\n    #session_id별로 생성된 새로운 특성 열들과 결측치가 -1로 채워진 데이터프레임 df를 생성 및 반환한다\n    df = pd.concat(dfs,axis=1) # dfs 안에 있는 df들을 가로방향으로 합쳐서 새로운 df를 생성한다\n    df = df.fillna(-1) # df의 결측치(NaN)를 -1로 채운다\n    #아래 두줄을 안하면 id가 level_group별로 나눠지지 않고\n    #각 값이 심각하게 크거나 음수가 나오는등 학습에 적합하지 않은 데이터가 될 수 있음\n    df = df.reset_index() # #index의 시작을 1로 변경 \n    df = df.set_index('session_id') # session_id를 새로운 인덱스로 설정한다\n    \n    return df","metadata":{"papermill":{"duration":0.017716,"end_time":"2023-02-07T01:00:59.136021","exception":false,"start_time":"2023-02-07T01:00:59.118305","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:36:46.649402Z","iopub.execute_input":"2023-07-25T05:36:46.649836Z","iopub.status.idle":"2023-07-25T05:36:46.666898Z","shell.execute_reply.started":"2023-07-25T05:36:46.649800Z","shell.execute_reply":"2023-07-25T05:36:46.665607Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%%time\n# %%time 위에는 아무것도 하면 안됨 주석만 달아도 오류\n# %%time은 해당 코드 블럭이 실행되는데 걸리는 시간을 측정해주는 주피터노트북의 매직커맨드 이다.\n\n# PROCESS TRAIN DATA IN PIECES\n# 데이터를 쪼개서 feature_engineer후 다시 붙임 메모리 초과를 방지하기 위함\n# 10개로 나눈 훈련 데이터를 훈련 진행시킨다\nall_pieces = []\nprint(f'Processing train as {PIECES} pieces to avoid memory error... ')\nfor k in range(PIECES):\n    print(k,', ',end='')\n    SKIPS = 0\n    if k>0: SKIPS = range(1,skips[k]+1) # 처음이 아니라면 1~ skips[k](이미 읽은 세션의 개수)의 범위를 가진다 \n    train = pd.read_csv('/kaggle/input/predict-student-performance-from-game-play/train.csv',\n                        nrows=reads[k], skiprows=SKIPS) # SKIPS 범위 내의 session_id를 스킵한 이후 reads의 k번째 범위에 속한 개수만큼 행을 읽어온다\n    df = feature_engineer(train) # train에 가져온 분석 안한 데이터들을 feature_engineer 함수에 넣어 분석하고\n    all_pieces.append(df) # 그 결과를 all_pieces list에 추가한다, 마지막에 all_pieces의 길이는 10이 된다\n\n# CONCATENATE ALL PIECES\nprint('\\n')\ndel train; gc.collect() #가비지 컬렉터를 수동 실행, train을 메모리에서 지운다\ndf = pd.concat(all_pieces, axis=0) #여러개의 feature_engineer()함수에서 리턴된 df들을 하나의 df로 합쳐준다\nprint('Shape of all train data after feature engineering:', df.shape ) #feature engineering된 새로운 df의 모양을 한번 찍어본다\ndf.head()","metadata":{"papermill":{"duration":34.516494,"end_time":"2023-02-07T01:01:33.658043","exception":false,"start_time":"2023-02-07T01:00:59.141549","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:36:46.668432Z","iopub.execute_input":"2023-07-25T05:36:46.669439Z","iopub.status.idle":"2023-07-25T05:44:35.783159Z","shell.execute_reply.started":"2023-07-25T05:36:46.669401Z","shell.execute_reply":"2023-07-25T05:44:35.782244Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Train XGBoost Model\n18개 문항 각각에 대해 하나의 모델을 훈련합니다. 또한, 1~3번 문항에 대한 모델 훈련에는 `level_groups = '0-4'`의 데이터를 사용하고, 4~13번 문항 훈련에는 `level groups '5-12'`, 14~18번 문항 훈련에는 `level groups '13-22'`의 데이터를 사용합니다. 이는 테스트 추론 중에 Kaggle의 추론 API에서 (해당 문제를 예측하기 위해) 얻은 데이터이기 때문입니다. 이전 'level_groups'에서 사용자의 이전 데이터를 저장하고 이를 사용하여 미래의 'level_groups'를 예측함으로써 모델을 개선할 수 있습니다.","metadata":{"papermill":{"duration":0.00565,"end_time":"2023-02-07T01:01:33.669525","exception":false,"start_time":"2023-02-07T01:01:33.663875","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# df에서 level_group 열을 제외한 나머지 모든 열 이름들을 리스트로 가져옴\nFEATURES = [c for c in df.columns if c != 'level_group']  # level_group 을 제외하고 Feature 만 모아줌\nprint('We will train with', len(FEATURES) ,'features')\nprint(FEATURES)\n#df의 index는 인덱스를 반환하며, unique는 중복값을 제거함. 즉 session_id의 고유 리스트를 구한다\nALL_USERS = df.index.unique()\nprint('We will train with', len(ALL_USERS) ,'users info')","metadata":{"papermill":{"duration":0.014699,"end_time":"2023-02-07T01:01:33.689953","exception":false,"start_time":"2023-02-07T01:01:33.675254","status":"completed"},"tags":[],"scrolled":true,"execution":{"iopub.status.busy":"2023-07-25T05:44:35.786000Z","iopub.execute_input":"2023-07-25T05:44:35.786736Z","iopub.status.idle":"2023-07-25T05:44:35.799830Z","shell.execute_reply.started":"2023-07-25T05:44:35.786699Z","shell.execute_reply":"2023-07-25T05:44:35.798432Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"objective : 최적화하려는 손실 함수\neval_metric : 모델을 평가하는데 사용되는 metric\nlearning_rate : 이전 결과를 얼마나 반영할지를 결정하는 값\nmax_depth : 생성되는 트리의 깊이를 제어하는 값\nn_estimators : 생성할 트리의 개수\nearly_stopping_rounds : 얼마나 빨리 학습을 중단할 것인지 결정하는 값\ntree_method : 트리를 생성하는데 사용되는 알고리즘 방식\nsubsample : 각 트리마다 사용할 데이터 샘플링 비율 (over-fitting 방지)\ncolsample_bytree : 각 트리마다 사용할 feature 샘플링 비율\nuse_label_encoder : XGBoost 내부의 label encoder 사용 여부 (default=True)","metadata":{}},{"cell_type":"code","source":"# k개의 fold로 나누어주는 K-fold 교차검증 중 하나로, 하나의 fold는 각기 다른 group에 의해 생성됨\n#n_splits 는 fold의 개수로, 5개의 fold로 데이터를 분할한다.\ngkf = GroupKFold(n_splits=6) \noof = pd.DataFrame(data=np.zeros((len(ALL_USERS),18)), index=ALL_USERS) # out of fold 예측 결과를 저장하기 위한 데이터프레임, 초기값은 모두 0인 (사용자 수 * 질문18개) 크기의 데이터프레임\nmodels = {}\n    \n# COMPUTE CV SCORE WITH 5 GROUP K FOLD\n# 아래 for문은 enumerate를 통해서 index(i)와 \nfor i, (train_index, test_index) in enumerate(gkf.split(X=df, groups=df.index)):\n    print('#'*25)\n    print('### Fold',i+1)\n    print('#'*25)\n    \n    #xgboost 파라미터 설정 \n    xgb_params = {} # xgboost의 버젼에 따라 기본값이 다르지만, 레이블 인코더를 사용할지 여부, False이면 One-Hot 인코딩 수행\n    \n    # ITERATE THRU QUESTIONS 1 THRU 18\n    # 18개의 그룹으로 분할후 훈련\n    for t in range(1,19):  \n        \n        # USE THIS TRAIN DATA WITH THESE QUESTIONS\n        # 질문 그룹별로 훈련 모델 생성 반복\n        if t<=3: grp = '0-4'# t: 1,2,3\n        elif t<=13: grp = '5-12' # t: 4,5,6,7,8,9,10,11,12,13\n        elif t<=22: grp = '13-22' # t: 14 15 16 17 18 19\n            \n        # TRAIN DATA\n        train_x = df.iloc[train_index]\n        train_x = train_x.loc[train_x.level_group == grp] # 질문 그룹이 동일한 부분만 가져온다\n        train_users = train_x.index.values # train_x의 session_id를 가져와서\n        train_y = targets.loc[targets.q==t].set_index('session').loc[train_users] #가져온 session_id의 이전 대답들을 가져온다\n        \n        # VALID DATA\n        valid_x = df.iloc[test_index]\n        valid_x = valid_x.loc[valid_x.level_group == grp]\n        valid_users = valid_x.index.values\n        valid_y = targets.loc[targets.q==t].set_index('session').loc[valid_users]\n        \n        # TRAIN MODEL\n        # TRAIN으로 학슴, TEST(Valid)로 검사  \n        clf =  XGBClassifier(**xgb_params) ## 딕셔너리인 xgb_params의 ket:value를 매개변수로 전달하기 위해 ** 사용\n        clf.fit(train_x[FEATURES].astype('float32'), train_y['correct'],\n                eval_set=[ (valid_x[FEATURES].astype('float32'), valid_y['correct']) ],\n                verbose=0) # 훈련시킨다\n        print(f'{t}({clf.best_ntree_limit}), ',end='')\n        \n        # SAVE MODEL, PREDICT VALID OOF\n        # 결과 저장\n        models[f'{grp}_{t}'] = clf\n        oof.loc[valid_users, t-1] = clf.predict_proba(valid_x[FEATURES].astype('float32'))[:,1]\n        \n    print() #줄바꿈용","metadata":{"papermill":{"duration":69.877213,"end_time":"2023-02-07T01:02:43.57299","exception":false,"start_time":"2023-02-07T01:01:33.695777","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:44:35.801649Z","iopub.execute_input":"2023-07-25T05:44:35.802172Z","iopub.status.idle":"2023-07-25T05:54:58.871996Z","shell.execute_reply.started":"2023-07-25T05:44:35.802122Z","shell.execute_reply":"2023-07-25T05:54:58.870774Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Compute CV(Cross Validation) Score\n예측 확률을 1과 0으로 변환하기 위해 최적의 임계값을 찾아 F1 점수를 최대화해야합니다. F1 점수는 정밀도와 재현율의 조화 평균입니다. 임계값을 설정하여 p > 임계값일 때 1로 예측하고 0으로 예측할 때 F1 점수를 최대화하는 방법을 찾을 것입니다.","metadata":{"papermill":{"duration":0.011241,"end_time":"2023-02-07T01:02:43.59638","exception":false,"start_time":"2023-02-07T01:02:43.585139","status":"completed"},"tags":[]}},{"cell_type":"markdown","source":"## 정밀도와 재현율\n\n- 정밀도 = Positive(1) 로 예측한 것 중에서 실제 Positive(1)인 비율 > TP/(TP+**FP**)\n- 재현율 = 실제 Positive(1) 중에서 정확하게 Positive(1)로 예측한 비율 > TP/(TP+**FN**)\n\n정밀도가 중요한 경우가 있고 재현율이 중요한 경우가 있다.\n\nPositive 를 Negative 로 판단하지 않는것이 중요 ⇒ 정밀도가 중요, FP로 얼마나 빠졌나..\n\n- 암이 아닌줄 알았는데 암이네?\n\nNegative 를 Positive 로 판단하지 않는것이 중요 ⇒ 재현율이 중요 FN으로 얼마나 빠졌나..\n\n- 스팸 메일인줄 알았는데 중요한 메일이네?\n\nF1 점수는 정밀도와 재현율의 **조화 평균** 이다\n\n![Untitled.png](attachment:328c07f7-189b-44d9-84e7-093d02819298.png)\n\n정밀도와 재현율의 평균이 **F1** 점수이기 때문에 보통 F1 점수가 높으면 성능이 높다고 할 수 있지만 위에 설명한 예시처럼 모델의 맥락에 따라 F1 점수가 중요하지 않을 수도 있다.\n\n정밀도와 재현율을 둘다 올리면 좋겠지만 보통 정밀도와 재현율은 반비례한다. 이를 **정밀도/재현율 트레이드오프** 라고 한다.\n\n![Untitled2.png](attachment:ea53627c-18e5-4aef-b1c0-1ad6ef9e23e2.png)","metadata":{},"attachments":{"328c07f7-189b-44d9-84e7-093d02819298.png":{"image/png":"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"},"ea53627c-18e5-4aef-b1c0-1ad6ef9e23e2.png":{"image/png":"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"}}},{"cell_type":"code","source":"# PUT TRUE LABELS INTO DATAFRAME WITH 18 COLUMNS\n# target값 true에 넣어서 비교 결과 만듬\ntrue = oof.copy()\nfor k in range(18):\n    # GET TRUE LABELS\n    tmp = targets.loc[targets.q == k+1].set_index('session').loc[ALL_USERS]\n    true[k] = tmp.correct.values","metadata":{"execution":{"iopub.status.busy":"2023-07-25T05:54:58.873339Z","iopub.execute_input":"2023-07-25T05:54:58.873988Z","iopub.status.idle":"2023-07-25T05:54:59.008537Z","shell.execute_reply.started":"2023-07-25T05:54:58.873951Z","shell.execute_reply":"2023-07-25T05:54:59.007105Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# FIND BEST THRESHOLD TO CONVERT PROBS INTO 1s AND 0s\nscores = []; thresholds = []\nbest_score = 0; best_threshold = 0\n\n#threshold값변화에 따른 예측값 측정후 최대 score와 그때 threshold값 저장\nfor threshold in np.arange(0.4,0.81,0.01):\n    print(f'{threshold:.02f}, ',end='')\n    preds = (oof.values.reshape((-1))>threshold).astype('int')\n    m = f1_score(true.values.reshape((-1)), preds, average='macro')   \n    scores.append(m)\n    thresholds.append(threshold)\n    if m>best_score:\n        best_score = m\n        best_threshold = threshold","metadata":{"execution":{"iopub.status.busy":"2023-07-25T05:54:59.010201Z","iopub.execute_input":"2023-07-25T05:54:59.010775Z","iopub.status.idle":"2023-07-25T05:55:07.523531Z","shell.execute_reply.started":"2023-07-25T05:54:59.010741Z","shell.execute_reply":"2023-07-25T05:55:07.522483Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\n\n# PLOT THRESHOLD VS. F1_SCORE\nplt.figure(figsize=(20,5))\nplt.plot(thresholds,scores,'-o',color='blue')\nplt.scatter([best_threshold], [best_score], color='blue', s=300, alpha=1)\nplt.xlabel('Threshold',size=14)\nplt.ylabel('Validation F1 Score',size=14)\nplt.title(f'Threshold vs. F1_Score with Best F1_Score = {best_score:.3f} at Best Threshold = {best_threshold:.3}',size=18)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-07-25T05:55:07.524963Z","iopub.execute_input":"2023-07-25T05:55:07.525291Z","iopub.status.idle":"2023-07-25T05:55:07.764329Z","shell.execute_reply.started":"2023-07-25T05:55:07.525261Z","shell.execute_reply":"2023-07-25T05:55:07.763274Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Threshold 값이 0.63 일때 F1 점수가 0.679로 가장 좋다","metadata":{}},{"cell_type":"code","source":"print('When using optimal threshold...')\nfor k in range(18):\n        \n    # COMPUTE F1 SCORE PER QUESTION\n    m = f1_score(true[k].values, (oof[k].values>best_threshold).astype('int'), average='macro')\n    print(f'Q{k}: F1 =',m)\n    \n# COMPUTE F1 SCORE OVERALL\nm = f1_score(true.values.reshape((-1)), (oof.values.reshape((-1))>best_threshold).astype('int'), average='macro')\nprint('==> Overall F1 =',m)","metadata":{"papermill":{"duration":0.771134,"end_time":"2023-02-07T01:02:44.378465","exception":false,"start_time":"2023-02-07T01:02:43.607331","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:55:07.766096Z","iopub.execute_input":"2023-07-25T05:55:07.766815Z","iopub.status.idle":"2023-07-25T05:55:08.177558Z","shell.execute_reply.started":"2023-07-25T05:55:07.766775Z","shell.execute_reply":"2023-07-25T05:55:08.176560Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Infer Test Data","metadata":{"papermill":{"duration":0.011075,"end_time":"2023-02-07T01:02:44.400918","exception":false,"start_time":"2023-02-07T01:02:44.389843","status":"completed"},"tags":[]}},{"cell_type":"code","source":"# IMPORT KAGGLE API\nimport jo_wilder\nenv = jo_wilder.make_env()\niter_test = env.iter_test()\n\n# CLEAR MEMORY\nimport gc\ndel targets, df, oof, true\n_ = gc.collect()","metadata":{"papermill":{"duration":0.052132,"end_time":"2023-02-07T01:02:44.464739","exception":false,"start_time":"2023-02-07T01:02:44.412607","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:55:08.179109Z","iopub.execute_input":"2023-07-25T05:55:08.179745Z","iopub.status.idle":"2023-07-25T05:55:08.229975Z","shell.execute_reply.started":"2023-07-25T05:55:08.179709Z","shell.execute_reply":"2023-07-25T05:55:08.226173Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"limits = {'0-4':(1,4), '5-12':(4,14), '13-22':(14,19)}\n\nfor (test, sample_submission) in iter_test:\n    \n    # FEATURE ENGINEER TEST DATA\n    df = feature_engineer(test)\n    \n    # INFER TEST DATA\n    grp = test.level_group.values[0]\n    a,b = limits[grp]\n    for t in range(a,b):\n        clf = models[f'{grp}_{t}']\n        p = clf.predict_proba(df[FEATURES].astype('float32'))[0,1]\n        mask = sample_submission.session_id.str.contains(f'q{t}')\n        sample_submission.loc[mask,'correct'] = int( p > best_threshold )\n    \n    env.predict(sample_submission)","metadata":{"papermill":{"duration":1.002014,"end_time":"2023-02-07T01:02:45.47927","exception":false,"start_time":"2023-02-07T01:02:44.477256","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:55:08.231530Z","iopub.status.idle":"2023-07-25T05:55:08.232057Z","shell.execute_reply.started":"2023-07-25T05:55:08.231805Z","shell.execute_reply":"2023-07-25T05:55:08.231844Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# EDA submission.csv","metadata":{"papermill":{"duration":0.011427,"end_time":"2023-02-07T01:02:45.502331","exception":false,"start_time":"2023-02-07T01:02:45.490904","status":"completed"},"tags":[]}},{"cell_type":"code","source":"df = pd.read_csv('submission.csv')\nprint( df.shape )\ndf.head()","metadata":{"papermill":{"duration":0.027432,"end_time":"2023-02-07T01:02:45.541022","exception":false,"start_time":"2023-02-07T01:02:45.51359","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:55:08.233800Z","iopub.status.idle":"2023-07-25T05:55:08.234241Z","shell.execute_reply.started":"2023-07-25T05:55:08.234031Z","shell.execute_reply":"2023-07-25T05:55:08.234051Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(df.correct.mean())","metadata":{"papermill":{"duration":0.020233,"end_time":"2023-02-07T01:02:45.57314","exception":false,"start_time":"2023-02-07T01:02:45.552907","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2023-07-25T05:55:08.235817Z","iopub.status.idle":"2023-07-25T05:55:08.236802Z","shell.execute_reply.started":"2023-07-25T05:55:08.236557Z","shell.execute_reply":"2023-07-25T05:55:08.236581Z"},"trusted":true},"execution_count":null,"outputs":[]}]}