User FrancoSwiss

19 votes

Is feature engineering still useful when using XGBoost?

answered Oct 3, 2017 at 6:27

7 votes

Should I oversample my validation data to get better F1 score and PRC?

answered Feb 23, 2019 at 8:38

6 votes

How to impute Missing values not the usual way?

answered Jan 11, 2020 at 12:56

5 votes

Why class weight is outperforming oversampling?

answered May 26, 2019 at 9:26

4 votes

What would I prefer - an over-fitted model or a less accurate model?

answered Jan 12, 2020 at 15:37

4 votes

Ways to simulate weather data over several periods (Python or R)?

answered Jan 24, 2020 at 6:49

4 votes

Handling outliers and Null values in Decision tree

answered Apr 7, 2019 at 9:17

3 votes

Coursera's course "How to Win a Data Science Competition"

answered May 26, 2019 at 14:36

2 votes

Automatically Remove highly correlated features using Variance Inflation Factor?

answered May 25, 2019 at 8:21

2 votes

Accuracy of the model

answered May 26, 2019 at 9:18

2 votes

Accepted

Why is my test data accuracy higher than my training data?

answered May 24, 2019 at 8:45

2 votes

Model biased towards low frequency data?

answered May 24, 2019 at 8:57

2 votes

How many trees does a Random Forest need?

answered Jan 24, 2020 at 20:40

2 votes

Accepted

Fastest way to relearn machine/deep learning

answered Jan 14, 2020 at 19:53

1 vote

Machine Learning methods for finding outliers

answered Jan 12, 2020 at 20:41

1 vote

How can one generate future forecasts from probabilistic events?

answered Jan 12, 2020 at 15:43

1 vote

Best way to combine two similar document

answered May 26, 2019 at 9:29

1 vote

Accepted

Connect Tableau and KoBoToolbox

answered Jan 11, 2020 at 19:40

1 vote

Feature Engineering

answered May 25, 2019 at 8:10

1 vote

Accepted

Installing skmca python package

answered May 25, 2019 at 8:12

1 vote

Event prediction sequence

answered May 25, 2019 at 8:17

1 vote

Dealing with a dataset with a mix of continuous and categorical variables

answered Feb 22, 2019 at 21:03

1 vote

How to match a user with another user based on their taste?

answered Feb 25, 2019 at 22:46

1 vote

Bad classification performance of logistic regression on imbalanced data in testing as compared to training

answered Feb 23, 2019 at 8:45

1 vote

In a binary classification, should the test dataset be balanced?

answered Feb 22, 2019 at 19:58

1 vote

Can Precision-Recall be improved for imbalanced sample?

answered Feb 22, 2019 at 20:05

1 vote

Accepted

About 1M rows of data. Should I restrict myself to few columns as well?

answered May 26, 2019 at 14:45

1 vote

why One-Hot Encoder can avoid the situation that the model will misunderstand the data to be in some kind of order if the data has been Label Encoding

answered May 26, 2019 at 14:57

1 vote

Elements of Statistical Learning - question on p. 18

answered May 29, 2019 at 8:14

1 vote

A doubt about the GridSearchCV function in Sklearn?

answered May 30, 2019 at 6:21

Stack Exchange Network

49 Answers

Is feature engineering still useful when using XGBoost?

Should I oversample my validation data to get better F1 score and PRC?

How to impute Missing values not the usual way?

Why class weight is outperforming oversampling?

What would I prefer - an over-fitted model or a less accurate model?

Ways to simulate weather data over several periods (Python or R)?

Handling outliers and Null values in Decision tree

Coursera's course "How to Win a Data Science Competition"

Automatically Remove highly correlated features using Variance Inflation Factor?

Accuracy of the model

Why is my test data accuracy higher than my training data?

Model biased towards low frequency data?

How many trees does a Random Forest need?

Fastest way to relearn machine/deep learning

Machine Learning methods for finding outliers

How can one generate future forecasts from probabilistic events?

Best way to combine two similar document

Connect Tableau and KoBoToolbox

Feature Engineering

Installing skmca python package

Event prediction sequence

Dealing with a dataset with a mix of continuous and categorical variables

How to match a user with another user based on their taste?

Bad classification performance of logistic regression on imbalanced data in testing as compared to training

In a binary classification, should the test dataset be balanced?

Can Precision-Recall be improved for imbalanced sample?

About 1M rows of data. Should I restrict myself to few columns as well?

why One-Hot Encoder can avoid the situation that the model will misunderstand the data to be in some kind of order if the data has been Label Encoding

Elements of Statistical Learning - question on p. 18

A doubt about the GridSearchCV function in Sklearn?