XGboost python - classifier class weight option?

For sklearn version < 0.19

Just assign each entry of your train data its class weight. First get the class weights with class_weight.compute_class_weight of sklearn then assign each row of the train data its appropriate weight.

I assume here that the train data has the column class containing the class number. I assumed also that there are nb_classes that are from 1 to nb_classes.

from sklearn.utils import class_weight
classes_weights = list(class_weight.compute_class_weight('balanced',
                                             np.unique(train_df['class']),
                                             train_df['class']))

weights = np.ones(y_train.shape[0], dtype = 'float')
for i, val in enumerate(y_train):
    weights[i] = classes_weights[val-1]

xgb_classifier.fit(X, y, sample_weight=weights)

Update for sklearn version >= 0.19

There is simpler solution

from sklearn.utils import class_weight
classes_weights = class_weight.compute_sample_weight(
    class_weight='balanced',
    y=train_df['class']
)

xgb_classifier.fit(X, y, sample_weight=classes_weights)

when using the sklearn wrapper, there is a parameter for weight.

example:

import xgboost as xgb
exgb_classifier = xgboost.XGBClassifier()
exgb_classifier.fit(X, y, sample_weight=sample_weights_data)

where the parameter shld be array like, length N, equal to the target length

I recently ran into this problem, so thought will leave a solution I tried

from xgboost import XGBClassifier

# manually handling imbalance. Below is same as computing float(18501)/392318 
on the trainig dataset.
# We are going to inversely assign the weights
weight_ratio = float(len(y_train[y_train == 0]))/float(len(y_train[y_train == 
1]))
w_array = np.array([1]*y_train.shape[0])
w_array[y_train==1] = weight_ratio
w_array[y_train==0] = 1- weight_ratio

xgc = XGBClassifier()
xgc.fit(x_df_i_p_filtered, y_train, sample_weight=w_array)

Not sure, why but the results were pretty disappointing. Hope this helps someone.

[Reference link] https://www.programcreek.com/python/example/99824/xgboost.XGBClassifier