Question

Let we try first Bernoulli naïve Bayes classifier (Here, 1 indicates that players can 'play'). #Import Bernoulli Naive Bayes model from sklearn.naive_bayes import GaussianNB, BernoulliNB #Create a Bernoulli Classifier model = BernoulliNB() # Train the model using the training sets model.fit(features_ls, label) #Predict Output predicted= model.predict([[0,2]]) # 0:Overcast, 2:Mild print ("Predicted Value:", predicted) Predicted Value: [1] Lab 9: Classification using Decision Trees & Naïve Bayes Exercise 2.3: Repeat the experiment again but now using Gaussian Naïve Bayes (just replace model= GaussianNB())! Is the result the same?

          Let we try first Bernoulli naïve Bayes classifier (Here, 1 indicates
that players can 'play').
#Import Bernoulli Naive Bayes model
from sklearn.naive_bayes import GaussianNB, BernoulliNB
#Create a Bernoulli Classifier
model = BernoulliNB()
# Train the model using the training sets
model.fit(features_ls, label)
#Predict Output
predicted= model.predict([[0,2]]) # 0:Overcast, 2:Mild
print ("Predicted Value:", predicted)
Predicted Value: [1]
Lab 9: Classification using Decision Trees & Naïve Bayes
Exercise 2.3: Repeat the experiment again but now using
Gaussian Naïve Bayes (just replace model= GaussianNB())!
Is the result the same?

Let we try first Bernoulli naïve Bayes classifier (Here, 1 indicates
that players can 'play').
#Import Bernoulli Naive Bayes model
from sklearn.naivebayes import GaussianNB, BernoulliNB
#Create a Bernoulli Classifier
model = BernoulliNB()
# Train the model using the training sets
model.fit(featuresls, label)
#Predict Output
predicted= model.predict([[0,2]]) # 0:Overcast, 2:Mild
print ("Predicted Value:", predicted)
Predicted Value: [1]
Lab 9: Classification using Decision Trees Naïve Bayes
Exercise 2.3: Repeat the experiment again but now using
Gaussian Naïve Bayes (just replace model= GaussianNB())!
Is the result the same?

Added by Hector R.

Question

Please give Ace some feedback