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oW_
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38 votes
Accepted

Adaboost vs Gradient Boosting

27 votes
Accepted

NLP - why is "not" a stop word?

22 votes
Accepted

How many features to sample using Random Forests

15 votes
Accepted

How to calculate VC-dimension?

13 votes
Accepted

Why isn't leaky ReLU always preferable to ReLU given the zero gradient for x<0?

11 votes
Accepted

How to find the count of consecutive same string values in a pandas dataframe?

9 votes

SGDClassifier: Online Learning/partial_fit with a previously unknown label

9 votes
Accepted

Regression: What defines Linear and non-linear models or functions

8 votes
Accepted

How to implement Python's MLPClassifier with gridsearchCV?

8 votes

Data science / machine learning books for mathematicians

8 votes
Accepted

Why do we pick random features in random forest

7 votes
Accepted

Pandas categorical variables encoding for regression (one-hot encoding vs dummy encoding)

7 votes

Incremental Learning with sklearn: warm_start, partial_fit(), fit()

6 votes

What makes binary cross entropy a better choice for binary classification than other loss functions?

6 votes

Why should we use (or not) dropout on the input layer?

6 votes
Accepted

Is Gini coefficient a good metric for measuring predictive model performance on highly imbalanced data

6 votes

Euclidean distance between time series in Python

6 votes

Are Decision Trees Robust to Outliers

5 votes
Accepted

Why not use Scaler.fit_transform on total dataframe?

5 votes

Using L1 penalty in XGBoost

5 votes
Accepted

What can functional programming be used for in data science?

5 votes
Accepted

How to further Interpret Variable Importance?

5 votes
Accepted

Muti-hot encoding vs Label-Encoding

5 votes
Accepted

Constant Learning Rate for Gradient Decent

5 votes
Accepted

How does class_weight work in Decision Tree

4 votes

XGBoost validation for number of trees

4 votes

Majority voting in scikit-learn Random forest

4 votes

Isolation Forest: simple example

4 votes

Effect of outliers on Naive Bayes

4 votes
Accepted

Why can decision trees have a high amount of variance?

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