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@rodrigols89
Created October 6, 2020 18:13
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import matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import cross_val_score # Cross Validation Function.
from sklearn.model_selection import KFold # KFold Class.
from sklearn.linear_model import LinearRegression # Linear Regression class.
df = pd.read_csv("../datasets/Admission_Predict.csv")
df.drop('Serial No.', axis = 1, inplace = True)
x = df.drop('Chance of Admit ', axis = 1)
y = df['Chance of Admit ']
model = LinearRegression()
kfold = KFold(n_splits=5, shuffle=True) # shuffle=True, Shuffle (embaralhar) the data.
result = cross_val_score(model, x, y, cv = kfold)
print("K-Fold (R^2) Scores: {0}".format(result))
print("Mean R^2 for Cross-Validation K-Fold: {0}".format(result.mean()))
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