{ "id": 540853, "title": "Using ChatGPT to Validate the Submission", "url": "/competitions/child-mind-institute-problematic-internet-use/discussion/540853", "author_name": "", "post_date": "2024-10-16T10:11:49.376828900Z", "votes": 2, "comment_count": 6, "views": 0, "content": "

Hello Kaggle community! On this occasion, I want to share a little contribution. My experience making ML models is very short, and I have much to learn; this is my first public competition participation.

\n

Then I had an idea: \"What if I ask ChatGPT for information on the submission to get a pseudo ML prediction?\" This is the result. I haven't verified if this prediction is accurate, but it can help if you run out of submission limits. You can use this to \"validate\" your results.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
idsiiJustification
00008ff92Given that the person's age is a positive factor and the CGAS score indicates moderate problems, the low BMI and concerns about growth suggest health risks.
000fd4602Given the concerns related to the low BMI and height, along with other health factors that could suggest nutritional problems.
1052581Given the overall health metrics, good blood pressure, relatively high emotional and social functioning, along with a BMI that, although low, does not indicate serious problems.
00115b9f2Taking into account the combination of a BMI indicating overweight, although with good blood pressure and a positive CGAS score.
0016bb221This indicates that, although there is concern about the low level of physical activity, the lack of information about other indicators prevents a more serious evaluation.
001f33793This indicates that the person presents several risk factors, including mental and physical health problems that require attention and possibly intervention. It is suggested to encourage a more active lifestyle, as well as to seek psychological and nutritional support to address this individual's overall health.
0038ba982The person presents some risk factors, especially with hypertension, that should be monitored and possibly addressed through lifestyle changes, such as increased physical activity and a healthier diet.
0068a4853The person has a reasonably good physical condition, with a healthy BMI and normal blood pressure. However, the lack of family support and unavailable mental health data suggest the need for follow-up. Additionally, although physical activity is moderate, it would be beneficial to increase it to ensure healthy development.
0069fbed1Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being.
0083e3971Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being.
00abe6552This level reflects that the person has adequate functioning overall, but with some areas that require attention, such as low levels of physical activity and possible mild emotional or behavioral challenges.
00ae59c93This classification reflects good physical condition and body composition, with a recommendation for follow-up on elevated blood pressure and the possibility of improvement in regular physical activity.
00af63872This classification reflects a low level of physical activity and overall performance in some areas. It is important to focus on improving physical activity to enhance cardiovascular performance, muscular strength, and flexibility.
00bd43590Given that there is a lack of data on physical and mental well-being (BMI, CGAS, cardiovascular status, physical activity), there are no clear indicators of severity. Based solely on age and moderate computer/internet use, no obvious problems are observed.
00c0cd712Although the CGAS score indicates moderate problems in social or school contexts, the most concerning factor is obesity (BMI of 29.32), which could have negative health consequences in the long term. Additionally, physical activity levels are low, although not concerning. There are no indicators of severe mental health problems (SDS in average range).
00d9913d1Although there are no significant data regarding psychosocial health (CGAS) or depression (SDS), the physical indicators point to a normal health status in terms of BMI and heart rate. However, waist circumference and low physical performance (low strength and few repetitions in lifts) could be signs that physical activity is limited, which may need attention, although it does not seem severe at this time.
00e6167c2This child has an elevated BMI that places him at risk for overweight issues. Although his body fat percentage is normal, waist circumference and low physical performance suggest the need to increase physical activity and maintain a more balanced diet. Excessive use of computers or the internet may also indicate a more sedentary lifestyle.
00ebc35d1The age is appropriate, but the lack of information on physical and mental health limits the evaluation. Without BMI, mental health (CGAS), or body composition information, there are no clear indications of serious problems.
", "messages": [ { "id": "3019154", "postDate": "10/16/2024 10:11:49", "content": "

Hello Kaggle community! On this occasion, I want to share a little contribution. My experience making ML models is very short, and I have much to learn; this is my first public competition participation.

\n

Then I had an idea: \"What if I ask ChatGPT for information on the submission to get a pseudo ML prediction?\" This is the result. I haven't verified if this prediction is accurate, but it can help if you run out of submission limits. You can use this to \"validate\" your results.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
idsiiJustification
00008ff92Given that the person's age is a positive factor and the CGAS score indicates moderate problems, the low BMI and concerns about growth suggest health risks.
000fd4602Given the concerns related to the low BMI and height, along with other health factors that could suggest nutritional problems.
1052581Given the overall health metrics, good blood pressure, relatively high emotional and social functioning, along with a BMI that, although low, does not indicate serious problems.
00115b9f2Taking into account the combination of a BMI indicating overweight, although with good blood pressure and a positive CGAS score.
0016bb221This indicates that, although there is concern about the low level of physical activity, the lack of information about other indicators prevents a more serious evaluation.
001f33793This indicates that the person presents several risk factors, including mental and physical health problems that require attention and possibly intervention. It is suggested to encourage a more active lifestyle, as well as to seek psychological and nutritional support to address this individual's overall health.
0038ba982The person presents some risk factors, especially with hypertension, that should be monitored and possibly addressed through lifestyle changes, such as increased physical activity and a healthier diet.
0068a4853The person has a reasonably good physical condition, with a healthy BMI and normal blood pressure. However, the lack of family support and unavailable mental health data suggest the need for follow-up. Additionally, although physical activity is moderate, it would be beneficial to increase it to ensure healthy development.
0069fbed1Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being.
0083e3971Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being.
00abe6552This level reflects that the person has adequate functioning overall, but with some areas that require attention, such as low levels of physical activity and possible mild emotional or behavioral challenges.
00ae59c93This classification reflects good physical condition and body composition, with a recommendation for follow-up on elevated blood pressure and the possibility of improvement in regular physical activity.
00af63872This classification reflects a low level of physical activity and overall performance in some areas. It is important to focus on improving physical activity to enhance cardiovascular performance, muscular strength, and flexibility.
00bd43590Given that there is a lack of data on physical and mental well-being (BMI, CGAS, cardiovascular status, physical activity), there are no clear indicators of severity. Based solely on age and moderate computer/internet use, no obvious problems are observed.
00c0cd712Although the CGAS score indicates moderate problems in social or school contexts, the most concerning factor is obesity (BMI of 29.32), which could have negative health consequences in the long term. Additionally, physical activity levels are low, although not concerning. There are no indicators of severe mental health problems (SDS in average range).
00d9913d1Although there are no significant data regarding psychosocial health (CGAS) or depression (SDS), the physical indicators point to a normal health status in terms of BMI and heart rate. However, waist circumference and low physical performance (low strength and few repetitions in lifts) could be signs that physical activity is limited, which may need attention, although it does not seem severe at this time.
00e6167c2This child has an elevated BMI that places him at risk for overweight issues. Although his body fat percentage is normal, waist circumference and low physical performance suggest the need to increase physical activity and maintain a more balanced diet. Excessive use of computers or the internet may also indicate a more sedentary lifestyle.
00ebc35d1The age is appropriate, but the lack of information on physical and mental health limits the evaluation. Without BMI, mental health (CGAS), or body composition information, there are no clear indications of serious problems.
", "rawMarkdown": "Hello Kaggle community! On this occasion, I want to share a little contribution. My experience making ML models is very short, and I have much to learn; this is my first public competition participation.\n\nThen I had an idea: \"What if I ask ChatGPT for information on the submission to get a pseudo ML prediction?\" This is the result. I haven't verified if this prediction is accurate, but it can help if you run out of submission limits. You can use this to \"validate\" your results.\n\n| **id** | **sii** | **Justification** |\n|---------------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| 00008ff9 | 2 | Given that the person's age is a positive factor and the CGAS score indicates moderate problems, the low BMI and concerns about growth suggest health risks. |\n| 000fd460 | 2 | Given the concerns related to the low BMI and height, along with other health factors that could suggest nutritional problems. |\n| 105258 | 1 | Given the overall health metrics, good blood pressure, relatively high emotional and social functioning, along with a BMI that, although low, does not indicate serious problems. |\n| 00115b9f | 2 | Taking into account the combination of a BMI indicating overweight, although with good blood pressure and a positive CGAS score. |\n| 0016bb22 | 1 | This indicates that, although there is concern about the low level of physical activity, the lack of information about other indicators prevents a more serious evaluation. |\n| 001f3379 | 3 | This indicates that the person presents several risk factors, including mental and physical health problems that require attention and possibly intervention. It is suggested to encourage a more active lifestyle, as well as to seek psychological and nutritional support to address this individual's overall health. |\n| 0038ba98 | 2 | The person presents some risk factors, especially with hypertension, that should be monitored and possibly addressed through lifestyle changes, such as increased physical activity and a healthier diet. |\n| 0068a485 | 3 | The person has a reasonably good physical condition, with a healthy BMI and normal blood pressure. However, the lack of family support and unavailable mental health data suggest the need for follow-up. Additionally, although physical activity is moderate, it would be beneficial to increase it to ensure healthy development. |\n| 0069fbed | 1 | Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being. |\n| 0083e397 | 1 | Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being. |\n| 00abe655 | 2 | This level reflects that the person has adequate functioning overall, but with some areas that require attention, such as low levels of physical activity and possible mild emotional or behavioral challenges. |\n| 00ae59c9 | 3 | This classification reflects good physical condition and body composition, with a recommendation for follow-up on elevated blood pressure and the possibility of improvement in regular physical activity. |\n| 00af6387 | 2 | This classification reflects a low level of physical activity and overall performance in some areas. It is important to focus on improving physical activity to enhance cardiovascular performance, muscular strength, and flexibility. |\n| 00bd4359 | 0 | Given that there is a lack of data on physical and mental well-being (BMI, CGAS, cardiovascular status, physical activity), there are no clear indicators of severity. Based solely on age and moderate computer/internet use, no obvious problems are observed. |\n| 00c0cd71 | 2 | Although the CGAS score indicates moderate problems in social or school contexts, the most concerning factor is obesity (BMI of 29.32), which could have negative health consequences in the long term. Additionally, physical activity levels are low, although not concerning. There are no indicators of severe mental health problems (SDS in average range). |\n| 00d9913d | 1 | Although there are no significant data regarding psychosocial health (CGAS) or depression (SDS), the physical indicators point to a normal health status in terms of BMI and heart rate. However, waist circumference and low physical performance (low strength and few repetitions in lifts) could be signs that physical activity is limited, which may need attention, although it does not seem severe at this time. |\n| 00e6167c | 2 | This child has an elevated BMI that places him at risk for overweight issues. Although his body fat percentage is normal, waist circumference and low physical performance suggest the need to increase physical activity and maintain a more balanced diet. Excessive use of computers or the internet may also indicate a more sedentary lifestyle. |\n| 00ebc35d | 1 | The age is appropriate, but the lack of information on physical and mental health limits the evaluation. Without BMI, mental health (CGAS), or body composition information, there are no clear indications of serious problems. |", "votes": null }, { "id": "3019350", "postDate": "10/16/2024 13:53:46", "content": "

Hi @jppower, can you show us the prompt you used when asking ChatGPT?

", "rawMarkdown": "Hi @jppower, can you show us the prompt you used when asking ChatGPT?", "votes": null }, { "id": "3019532", "postDate": "10/16/2024 16:34:33", "content": "

Well, first I downloaded the test data and manipulated the file in Excel. Then, I transposed the data and asked one by one.
\nFirst, I entered the person's data, e.g.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FeaturesValues
ID000fd460
Basic_Demos-Enroll_SeasonSummer
Basic_Demos-Age9
Basic_Demos-Sex0
CGAS-SeasonNaN
CGAS-CGAS_ScoreNaN
Physical-SeasonFall
Physical-BMI14.03559028
Physical-Height48
Physical-Weight46
Physical-Waist_Circumference22
Physical-Diastolic_BP75
Physical-HeartRate70
Physical-Systolic_BP122
Fitness_Endurance-SeasonNaN
Fitness_Endurance-Max_StageNaN
Fitness_Endurance-Time_MinsNaN
Fitness_Endurance-Time_SecNaN
FGC-SeasonFall
FGC-FGC_CU3
FGC-FGC_CU_Zone0
FGC-FGC_GSNDNaN
FGC-FGC_GSND_ZoneNaN
FGC-FGC_GSDNaN
FGC-FGC_GSD_ZoneNaN
FGC-FGC_PU5
FGC-FGC_PU_Zone0
FGC-FGC_SRL11
FGC-FGC_SRL_Zone1
FGC-FGC_SRR11
FGC-FGC_SRR_Zone1
FGC-FGC_TL3
FGC-FGC_TL_Zone0
BIA-SeasonWinter
BIA-BIA_Activity_Level_num2
BIA-BIA_BMC2.57949
BIA-BIA_BMI14.0371
BIA-BIA_BMR936.656
BIA-BIA_DEE1498.65
BIA-BIA_ECW6.01993
BIA-BIA_FFM42.0291
BIA-BIA_FFMI12.8254
BIA-BIA_FMI1.21172
BIA-BIA_Fat3.97085
BIA-BIA_Frame_num1
BIA-BIA_ICW21.0352
BIA-BIA_LDM14.974
BIA-BIA_LST39.4497
BIA-BIA_SMM15.4107
BIA-BIA_TBW27.0552
PAQ_A-SeasonNaN
PAQ_A-PAQ_A_TotalNaN
PAQ_C-SeasonFall
PAQ_C-PAQ_C_Total2.34
SDS-SeasonFall
SDS-SDS_Total_Raw46
SDS-SDS_Total_T64
PreInt_EduHx-SeasonSummer
PreInt_EduHx-computerinternet_hoursday0
\n

Then I asked someone something like, \"This person is on a scale from 0, where 0 is not bad, to 3, which is very bad. Where would you classify them?\"

", "rawMarkdown": "Well, first I downloaded the test data and manipulated the file in Excel. Then, I transposed the data and asked one by one.\nFirst, I entered the person's data, e.g.\n\n| **Features** | **Values** |\n|----------------------------------------|-------------------|\n| **ID** | 000fd460 |\n| **Basic_Demos-Enroll_Season** | Summer |\n| **Basic_Demos-Age** | 9 |\n| **Basic_Demos-Sex** | 0 |\n| **CGAS-Season** | NaN |\n| **CGAS-CGAS_Score** | NaN |\n| **Physical-Season** | Fall |\n| **Physical-BMI** | 14.03559028 |\n| **Physical-Height** | 48 |\n| **Physical-Weight** | 46 |\n| **Physical-Waist_Circumference** | 22 |\n| **Physical-Diastolic_BP** | 75 |\n| **Physical-HeartRate** | 70 |\n| **Physical-Systolic_BP** | 122 |\n| **Fitness_Endurance-Season** | NaN |\n| **Fitness_Endurance-Max_Stage** | NaN |\n| **Fitness_Endurance-Time_Mins** | NaN |\n| **Fitness_Endurance-Time_Sec** | NaN |\n| **FGC-Season** | Fall |\n| **FGC-FGC_CU** | 3 |\n| **FGC-FGC_CU_Zone** | 0 |\n| **FGC-FGC_GSND** | NaN |\n| **FGC-FGC_GSND_Zone** | NaN |\n| **FGC-FGC_GSD** | NaN |\n| **FGC-FGC_GSD_Zone** | NaN |\n| **FGC-FGC_PU** | 5 |\n| **FGC-FGC_PU_Zone** | 0 |\n| **FGC-FGC_SRL** | 11 |\n| **FGC-FGC_SRL_Zone** | 1 |\n| **FGC-FGC_SRR** | 11 |\n| **FGC-FGC_SRR_Zone** | 1 |\n| **FGC-FGC_TL** | 3 |\n| **FGC-FGC_TL_Zone** | 0 |\n| **BIA-Season** | Winter |\n| **BIA-BIA_Activity_Level_num** | 2 |\n| **BIA-BIA_BMC** | 2.57949 |\n| **BIA-BIA_BMI** | 14.0371 |\n| **BIA-BIA_BMR** | 936.656 |\n| **BIA-BIA_DEE** | 1498.65 |\n| **BIA-BIA_ECW** | 6.01993 |\n| **BIA-BIA_FFM** | 42.0291 |\n| **BIA-BIA_FFMI** | 12.8254 |\n| **BIA-BIA_FMI** | 1.21172 |\n| **BIA-BIA_Fat** | 3.97085 |\n| **BIA-BIA_Frame_num** | 1 |\n| **BIA-BIA_ICW** | 21.0352 |\n| **BIA-BIA_LDM** | 14.974 |\n| **BIA-BIA_LST** | 39.4497 |\n| **BIA-BIA_SMM** | 15.4107 |\n| **BIA-BIA_TBW** | 27.0552 |\n| **PAQ_A-Season** | NaN |\n| **PAQ_A-PAQ_A_Total** | NaN |\n| **PAQ_C-Season** | Fall |\n| **PAQ_C-PAQ_C_Total** | 2.34 |\n| **SDS-Season** | Fall |\n| **SDS-SDS_Total_Raw** | 46 |\n| **SDS-SDS_Total_T** | 64 |\n| **PreInt_EduHx-Season** | Summer |\n| **PreInt_EduHx-computerinternet_hoursday** | 0 |\n\n\n\nThen I asked someone something like, \"This person is on a scale from 0, where 0 is not bad, to 3, which is very bad. Where would you classify them?\"", "votes": null }, { "id": "3020770", "postDate": "10/17/2024 21:46:13", "content": "

I think this approach will be very average in terms of performance.
\nIt might give more weightage to those features which in the data distribution might haven't given that much weight.

", "rawMarkdown": "I think this approach will be very average in terms of performance. \nIt might give more weightage to those features which in the data distribution might haven't given that much weight.", "votes": null }, { "id": "3021378", "postDate": "10/18/2024 12:45:35", "content": "

If I remember correctly, around 8 or 10 of the sample test data come from the train set. They have same id.
\nI have asked ChatGPT/ Copilot more than 500 questions last week I guess. Very good at cleaning code but not too well in providing insight, yet.
\nSearching the Kaggle discussions seems to be more fruitful. Many discussion about feature engineering/ imbalanced data.

", "rawMarkdown": "If I remember correctly, around 8 or 10 of the sample test data come from the train set. They have same id.\nI have asked ChatGPT/ Copilot more than 500 questions last week I guess. Very good at cleaning code but not too well in providing insight, yet.\nSearching the Kaggle discussions seems to be more fruitful. Many discussion about feature engineering/ imbalanced data.", "votes": null }, { "id": "3021788", "postDate": "10/18/2024 20:59:06", "content": "

Thank you so much for your contribution! It's very helpful to hear about your experience. You're absolutely right—ChatGPT can sometimes be a bit biased or limited when it comes to deeper insights, as it's mainly designed to assist with code and general queries. However, part of the goal was to experiment with new ways to gain insights, even if it's not perfect yet.

", "rawMarkdown": "Thank you so much for your contribution! It's very helpful to hear about your experience. You're absolutely right—ChatGPT can sometimes be a bit biased or limited when it comes to deeper insights, as it's mainly designed to assist with code and general queries. However, part of the goal was to experiment with new ways to gain insights, even if it's not perfect yet.", "votes": null }, { "id": "3021795", "postDate": "10/18/2024 21:03:52", "content": "

Thank you very much for your contribution! It was more of an idea I wanted to bring into the discussion. Your insights are really valuable, and congratulations on being ranked 23rd in the competition!

", "rawMarkdown": "Thank you very much for your contribution! It was more of an idea I wanted to bring into the discussion. Your insights are really valuable, and congratulations on being ranked 23rd in the competition!", "votes": null } ], "comments": [ { "id": 3019350, "author_name": "ambrosm", "author_url": "", "post_date": "10/16/2024 13:53:46", "content": "

Hi @jppower, can you show us the prompt you used when asking ChatGPT?

", "votes": null, "replies": [ { "id": 3019532, "author_name": "jppower", "author_url": "", "post_date": "10/16/2024 16:34:33", "content": "

Well, first I downloaded the test data and manipulated the file in Excel. Then, I transposed the data and asked one by one.
\nFirst, I entered the person's data, e.g.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FeaturesValues
ID000fd460
Basic_Demos-Enroll_SeasonSummer
Basic_Demos-Age9
Basic_Demos-Sex0
CGAS-SeasonNaN
CGAS-CGAS_ScoreNaN
Physical-SeasonFall
Physical-BMI14.03559028
Physical-Height48
Physical-Weight46
Physical-Waist_Circumference22
Physical-Diastolic_BP75
Physical-HeartRate70
Physical-Systolic_BP122
Fitness_Endurance-SeasonNaN
Fitness_Endurance-Max_StageNaN
Fitness_Endurance-Time_MinsNaN
Fitness_Endurance-Time_SecNaN
FGC-SeasonFall
FGC-FGC_CU3
FGC-FGC_CU_Zone0
FGC-FGC_GSNDNaN
FGC-FGC_GSND_ZoneNaN
FGC-FGC_GSDNaN
FGC-FGC_GSD_ZoneNaN
FGC-FGC_PU5
FGC-FGC_PU_Zone0
FGC-FGC_SRL11
FGC-FGC_SRL_Zone1
FGC-FGC_SRR11
FGC-FGC_SRR_Zone1
FGC-FGC_TL3
FGC-FGC_TL_Zone0
BIA-SeasonWinter
BIA-BIA_Activity_Level_num2
BIA-BIA_BMC2.57949
BIA-BIA_BMI14.0371
BIA-BIA_BMR936.656
BIA-BIA_DEE1498.65
BIA-BIA_ECW6.01993
BIA-BIA_FFM42.0291
BIA-BIA_FFMI12.8254
BIA-BIA_FMI1.21172
BIA-BIA_Fat3.97085
BIA-BIA_Frame_num1
BIA-BIA_ICW21.0352
BIA-BIA_LDM14.974
BIA-BIA_LST39.4497
BIA-BIA_SMM15.4107
BIA-BIA_TBW27.0552
PAQ_A-SeasonNaN
PAQ_A-PAQ_A_TotalNaN
PAQ_C-SeasonFall
PAQ_C-PAQ_C_Total2.34
SDS-SeasonFall
SDS-SDS_Total_Raw46
SDS-SDS_Total_T64
PreInt_EduHx-SeasonSummer
PreInt_EduHx-computerinternet_hoursday0
\n

Then I asked someone something like, \"This person is on a scale from 0, where 0 is not bad, to 3, which is very bad. Where would you classify them?\"

", "votes": null, "replies": [] } ] }, { "id": 3020770, "author_name": "chanpreetsingh07", "author_url": "", "post_date": "10/17/2024 21:46:13", "content": "

I think this approach will be very average in terms of performance.
\nIt might give more weightage to those features which in the data distribution might haven't given that much weight.

", "votes": null, "replies": [ { "id": 3021795, "author_name": "jppower", "author_url": "", "post_date": "10/18/2024 21:03:52", "content": "

Thank you very much for your contribution! It was more of an idea I wanted to bring into the discussion. Your insights are really valuable, and congratulations on being ranked 23rd in the competition!

", "votes": null, "replies": [] } ] }, { "id": 3021378, "author_name": "tomyuen", "author_url": "", "post_date": "10/18/2024 12:45:35", "content": "

If I remember correctly, around 8 or 10 of the sample test data come from the train set. They have same id.
\nI have asked ChatGPT/ Copilot more than 500 questions last week I guess. Very good at cleaning code but not too well in providing insight, yet.
\nSearching the Kaggle discussions seems to be more fruitful. Many discussion about feature engineering/ imbalanced data.

", "votes": null, "replies": [ { "id": 3021788, "author_name": "jppower", "author_url": "", "post_date": "10/18/2024 20:59:06", "content": "

Thank you so much for your contribution! It's very helpful to hear about your experience. You're absolutely right—ChatGPT can sometimes be a bit biased or limited when it comes to deeper insights, as it's mainly designed to assist with code and general queries. However, part of the goal was to experiment with new ways to gain insights, even if it's not perfect yet.

", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "3019154": "Hello Kaggle community! On this occasion, I want to share a little contribution. My experience making ML models is very short, and I have much to learn; this is my first public competition participation.\n\nThen I had an idea: \"What if I ask ChatGPT for information on the submission to get a pseudo ML prediction?\" This is the result. I haven't verified if this prediction is accurate, but it can help if you run out of submission limits. You can use this to \"validate\" your results.\n\n| **id** | **sii** | **Justification** |\n|---------------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| 00008ff9 | 2 | Given that the person's age is a positive factor and the CGAS score indicates moderate problems, the low BMI and concerns about growth suggest health risks. |\n| 000fd460 | 2 | Given the concerns related to the low BMI and height, along with other health factors that could suggest nutritional problems. |\n| 105258 | 1 | Given the overall health metrics, good blood pressure, relatively high emotional and social functioning, along with a BMI that, although low, does not indicate serious problems. |\n| 00115b9f | 2 | Taking into account the combination of a BMI indicating overweight, although with good blood pressure and a positive CGAS score. |\n| 0016bb22 | 1 | This indicates that, although there is concern about the low level of physical activity, the lack of information about other indicators prevents a more serious evaluation. |\n| 001f3379 | 3 | This indicates that the person presents several risk factors, including mental and physical health problems that require attention and possibly intervention. It is suggested to encourage a more active lifestyle, as well as to seek psychological and nutritional support to address this individual's overall health. |\n| 0038ba98 | 2 | The person presents some risk factors, especially with hypertension, that should be monitored and possibly addressed through lifestyle changes, such as increased physical activity and a healthier diet. |\n| 0068a485 | 3 | The person has a reasonably good physical condition, with a healthy BMI and normal blood pressure. However, the lack of family support and unavailable mental health data suggest the need for follow-up. Additionally, although physical activity is moderate, it would be beneficial to increase it to ensure healthy development. |\n| 0069fbed | 1 | Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being. |\n| 0083e397 | 1 | Due to the lack of significant data in critical areas of physical and mental health, as well as the absence of information on family support and physical activity, this person's condition cannot be adequately evaluated. It is recommended to gather additional information for a clearer view of the person's overall status and well-being. |\n| 00abe655 | 2 | This level reflects that the person has adequate functioning overall, but with some areas that require attention, such as low levels of physical activity and possible mild emotional or behavioral challenges. |\n| 00ae59c9 | 3 | This classification reflects good physical condition and body composition, with a recommendation for follow-up on elevated blood pressure and the possibility of improvement in regular physical activity. |\n| 00af6387 | 2 | This classification reflects a low level of physical activity and overall performance in some areas. It is important to focus on improving physical activity to enhance cardiovascular performance, muscular strength, and flexibility. |\n| 00bd4359 | 0 | Given that there is a lack of data on physical and mental well-being (BMI, CGAS, cardiovascular status, physical activity), there are no clear indicators of severity. Based solely on age and moderate computer/internet use, no obvious problems are observed. |\n| 00c0cd71 | 2 | Although the CGAS score indicates moderate problems in social or school contexts, the most concerning factor is obesity (BMI of 29.32), which could have negative health consequences in the long term. Additionally, physical activity levels are low, although not concerning. There are no indicators of severe mental health problems (SDS in average range). |\n| 00d9913d | 1 | Although there are no significant data regarding psychosocial health (CGAS) or depression (SDS), the physical indicators point to a normal health status in terms of BMI and heart rate. However, waist circumference and low physical performance (low strength and few repetitions in lifts) could be signs that physical activity is limited, which may need attention, although it does not seem severe at this time. |\n| 00e6167c | 2 | This child has an elevated BMI that places him at risk for overweight issues. Although his body fat percentage is normal, waist circumference and low physical performance suggest the need to increase physical activity and maintain a more balanced diet. Excessive use of computers or the internet may also indicate a more sedentary lifestyle. |\n| 00ebc35d | 1 | The age is appropriate, but the lack of information on physical and mental health limits the evaluation. Without BMI, mental health (CGAS), or body composition information, there are no clear indications of serious problems. |", "3019350": "Hi @jppower, can you show us the prompt you used when asking ChatGPT?", "3019532": "Well, first I downloaded the test data and manipulated the file in Excel. Then, I transposed the data and asked one by one.\nFirst, I entered the person's data, e.g.\n\n| **Features** | **Values** |\n|----------------------------------------|-------------------|\n| **ID** | 000fd460 |\n| **Basic_Demos-Enroll_Season** | Summer |\n| **Basic_Demos-Age** | 9 |\n| **Basic_Demos-Sex** | 0 |\n| **CGAS-Season** | NaN |\n| **CGAS-CGAS_Score** | NaN |\n| **Physical-Season** | Fall |\n| **Physical-BMI** | 14.03559028 |\n| **Physical-Height** | 48 |\n| **Physical-Weight** | 46 |\n| **Physical-Waist_Circumference** | 22 |\n| **Physical-Diastolic_BP** | 75 |\n| **Physical-HeartRate** | 70 |\n| **Physical-Systolic_BP** | 122 |\n| **Fitness_Endurance-Season** | NaN |\n| **Fitness_Endurance-Max_Stage** | NaN |\n| **Fitness_Endurance-Time_Mins** | NaN |\n| **Fitness_Endurance-Time_Sec** | NaN |\n| **FGC-Season** | Fall |\n| **FGC-FGC_CU** | 3 |\n| **FGC-FGC_CU_Zone** | 0 |\n| **FGC-FGC_GSND** | NaN |\n| **FGC-FGC_GSND_Zone** | NaN |\n| **FGC-FGC_GSD** | NaN |\n| **FGC-FGC_GSD_Zone** | NaN |\n| **FGC-FGC_PU** | 5 |\n| **FGC-FGC_PU_Zone** | 0 |\n| **FGC-FGC_SRL** | 11 |\n| **FGC-FGC_SRL_Zone** | 1 |\n| **FGC-FGC_SRR** | 11 |\n| **FGC-FGC_SRR_Zone** | 1 |\n| **FGC-FGC_TL** | 3 |\n| **FGC-FGC_TL_Zone** | 0 |\n| **BIA-Season** | Winter |\n| **BIA-BIA_Activity_Level_num** | 2 |\n| **BIA-BIA_BMC** | 2.57949 |\n| **BIA-BIA_BMI** | 14.0371 |\n| **BIA-BIA_BMR** | 936.656 |\n| **BIA-BIA_DEE** | 1498.65 |\n| **BIA-BIA_ECW** | 6.01993 |\n| **BIA-BIA_FFM** | 42.0291 |\n| **BIA-BIA_FFMI** | 12.8254 |\n| **BIA-BIA_FMI** | 1.21172 |\n| **BIA-BIA_Fat** | 3.97085 |\n| **BIA-BIA_Frame_num** | 1 |\n| **BIA-BIA_ICW** | 21.0352 |\n| **BIA-BIA_LDM** | 14.974 |\n| **BIA-BIA_LST** | 39.4497 |\n| **BIA-BIA_SMM** | 15.4107 |\n| **BIA-BIA_TBW** | 27.0552 |\n| **PAQ_A-Season** | NaN |\n| **PAQ_A-PAQ_A_Total** | NaN |\n| **PAQ_C-Season** | Fall |\n| **PAQ_C-PAQ_C_Total** | 2.34 |\n| **SDS-Season** | Fall |\n| **SDS-SDS_Total_Raw** | 46 |\n| **SDS-SDS_Total_T** | 64 |\n| **PreInt_EduHx-Season** | Summer |\n| **PreInt_EduHx-computerinternet_hoursday** | 0 |\n\n\n\nThen I asked someone something like, \"This person is on a scale from 0, where 0 is not bad, to 3, which is very bad. Where would you classify them?\"", "3020770": "I think this approach will be very average in terms of performance. \nIt might give more weightage to those features which in the data distribution might haven't given that much weight.", "3021378": "If I remember correctly, around 8 or 10 of the sample test data come from the train set. They have same id.\nI have asked ChatGPT/ Copilot more than 500 questions last week I guess. Very good at cleaning code but not too well in providing insight, yet.\nSearching the Kaggle discussions seems to be more fruitful. Many discussion about feature engineering/ imbalanced data.", "3021788": "Thank you so much for your contribution! It's very helpful to hear about your experience. You're absolutely right—ChatGPT can sometimes be a bit biased or limited when it comes to deeper insights, as it's mainly designed to assist with code and general queries. However, part of the goal was to experiment with new ways to gain insights, even if it's not perfect yet.", "3021795": "Thank you very much for your contribution! It was more of an idea I wanted to bring into the discussion. Your insights are really valuable, and congratulations on being ranked 23rd in the competition!" }, "source": "meta" }