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To do the following we need to follow these steps. Get the vectorized matrix print("Final Data-matrix:") print(X_tr.shape, y_train.shape)…
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Conditional probability uses Bayes theorem to calculate the relationships between the dependent events. If A and B are two events then P(A\B) can be…
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It is simple to work on mutually exclusive cases but most of the actual problems belong to non-mutually exclusive events. We can predict the event…
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Explain Naïve Bayes By Building A Spam Classifier In Python
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First we import the training and testing data # Importing the dataset training_set = read.csv(file.choose())#salary_train test_set =…
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First we import the libraries and the datasets import pandas as pd import bumpy as np from sklearn.naive_bayes import Gaussian NB from…
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Let us create an empty list which will contain the training and testing accuracy and the respective k values. The following code will generate the k…
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Stop words really matter in text p reprocessing problem but when it comes to sentiment analysis, stop words can create a lot of problems. It can…
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To implement Naïve Bayes from scratch, let us take the following example. Initially we import the following libraries and the dataset.…
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Let us create an empty list which will contain the training and testing accuracy and the respective k values. The following code will generate the k…
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We will be analyzing increase of dimensional with 60 random points. 2D example<
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Initially, we will import the dataset # Importing the dataset dataset = read.csv('Social_Network_Ads.csv') dataset = dataset[3:5] Let us see the head…
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