1. Create a naive Bayes model for this data set.



2. What prediction will the naive Bayes model return for the query q=(1,0,0)?

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Answer:

import the GaussianNB class from the scikit-learn naive bayes module using the import statement;

from sklearn.naivebayes import GaussianNB

create the classifier,

clf = GaussianNB()

Then train or fit a section of the dataset (the training set) with the classifier, then predict the label of the test section of the dataset with the provided query "q".

trained = clf.fit( train_features, train_label)

predict = clf.predict(q)

Explanation:

The scikit-learn is a machine learning package in python used to create machine models from datasets. It has several classifiers and regressions algorithms.

The naive baye algorithm is a machine learning class in python used in supervised machine learning to create models used to predict a label given a set of features using a classifier.

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System.out.print();

System.out.print("Enter a number less than
100: ");

num = Expo.enterInt();


for (int i=1; I <= num; I++){

if(num %2!=0)

System.out.println(num + " is odd");
else

System.ouy.println(num +"is even")

}

System.out.println();
}
}

Say I enter 5. The loop makes 5 show up 5 times instead of the numbers 1-5 saying if it's even or odd​

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