Showing posts with the label MACHINE LEARNING
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To Write a program to implement k-Nearest Neighbour algorithm to classify the iris data set. Print both correct and wrong predictions. Java/Python ML library classes can be used for this problem.
Program import csv import random import math import operator def loadDataset(filename, split, trai…
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To Apply EM algorithm to cluster a set of data stored in a .CSV file. Use the same data set for clustering using k-Means algorithm. Compare the results of these two algorithms and comment on the quality of clustering. You can add Java/Python ML library classes/API in the program.
Program import numpy as np import matplotlib.pyplot as plt from sklearn.datasets.samples_generator…
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To Write a program to construct a Bayesian network considering medical data. Use this model to demonstrate the diagnosis of heart patients using standard Heart Disease Data Set. You can use Java/Python ML library classes/API.
Program From pomegranate import* Asia=DiscreteDistribution({ „True‟:0.5, „False‟:0.5 }) Tubercul…
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To Assuming a set of documents that need to be classified, use the naïve Bayesian Classifier model to perform this task. Built-in Java classes/API can be used to write the program. Calculate the accuracy, precision, and recall for your data set.
Program import pandas as pd msg=pd.read_csv('naivetext1.csv',names=['message','…
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To Write a program to implement the naïve Bayesian classifier for a sample training data set stored as a .CSV file. Compute the accuracy of the classifier, considering few test data sets.
Program import csv import random import math def loadCsv(filename): lines = csv.reader(open(filena…
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