Local validation

Winning a Kaggle Competition in Python

Yauhen Babakhin

Kaggle Grandmaster

Motivation

overfitting example with Public and Private leaderboards

Holdout set

holdout set scheme

Holdout set

holdout set scheme

Holdout set

holdout set scheme

K-fold cross-validation

split train data into four folds

K-fold cross-validation

k-fold cross validation scheme

K-fold cross-validation

# Import KFold
from sklearn.model_selection import KFold

# Create a KFold object
kf = KFold(n_splits=5, shuffle=True, random_state=123)

# Loop through each cross-validation split
for train_index, test_index in kf.split(train):

    # Get training and testing data for the corresponding split
    cv_train, cv_test = train.iloc[train_index], train.iloc[test_index]

Stratified K-fold

stratified k-fold cross validation scheme

Stratified K-fold

# Import StratifiedKFold
from sklearn.model_selection import StratifiedKFold


# Create a StratifiedKFold object
str_kf = StratifiedKFold(n_splits=5, shuffle=True, random_state=123)


# Loop through each cross-validation split
for train_index, test_index in str_kf.split(train, train['target']):
    cv_train, cv_test = train.iloc[train_index], train.iloc[test_index]

Let's practice!

Winning a Kaggle Competition in Python