January 2020
Beginner to intermediate
432 pages
11h 24m
English
Content preview from Python for Finance Cookbook
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How to do it...
Execute the following steps to split the dataset into training and test sets.
- Import the function from sklearn:
from sklearn.model_selection import train_test_split
- Split the data into training and test sets:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
- Split the data into training and test sets without shuffling:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, shuffle=False)
- Split the data into training and test sets with stratification:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, stratify=y, random_state=42)
- Verify that the ratio of the target is preserved:
y_train.value_counts(normalize=True)y_test.value_counts(normalize=True) ...
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