Python 的行銷機器學習
Karolis Urbonas
Head of Analytics & Science, Amazon
主要的流失分類依兩種商業模式:


通常:
Churn/No Churn 或 Yes/No——最佳做法是轉成 1 與 0set(telcom['Churn'])
{0, 1}
telcom.groupby(['Churn']).size() / telcom.shape[0] * 100
Churn
0 73.421502
1 26.578498
dtype: float64
from sklearn.model_selection import train_test_split
train, test = train_test_split(telcom, test_size = .25)
依資料型別分出欄位名稱
target = ['Churn']
custid = ['customerID']
cols = [col for col in telcom.columns if col not in custid + target]
建立訓練與測試資料集
train_X = train[cols]
train_Y = train[target]
test_X = test[cols]
test_Y = test[target]
Python 的行銷機器學習