train,test,dev python
import numpy as np
import pandas as pd
def train_validate_test_split(df, train_percent=.6, validate_percent=.2, seed=None):
np.random.seed(seed)
perm = np.random.permutation(df.index)
m = len(df.index)
train_end = int(train_percent * m)
validate_end = int(validate_percent * m) + train_end
train = df.iloc[perm[:train_end]]
validate = df.iloc[perm[train_end:validate_end]]
test = df.iloc[perm[validate_end:]]
return train, validate, testtrain test split
from sklearn.linear_model import LinearRegression
rl = LinearRegression().fit(X, y)
rl.fit(X, y) #We can fit model to dataset in this way tooCopyright © 2021 Codeinu
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