Gaussian-Analysis
Sat 17 May 2025
from sklearn.naive_bayes import GaussianNB
import numpy as np
#assigning predictor and target variables
x= np.array([[-3,7],[1,5], [1,2], [-2,0], [2,3], [-4,0], [-1,1], [1,1], [-2,2], [2,7], [-4,1], [-2,7]])
y = np.array([3, 3, 3, 3, 4, 3, 3, 4, 3, 4, 4, 4])
#Create a Gaussian Classifier
model = GaussianNB()
# Train the model using the training sets
model.fit(x, y)
GaussianNB()In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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GaussianNB()
#Predict Output
predicted= model.predict([[1,2],[3,4]])
print(predicted)
[3 4]
Score: 5
Category: sklearn