Decision Tree using CART algorithm Solved Example 2 – Loan Approval Data Set In this tutorial, we will understand how to apply Classification And Regression Trees (CART) decision tree algorithm (Solved Example 2) to construct and find the optimal decision tree for the given Loan Approval Data set. Also, predict the class label for the […]
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Decision Tree using CART algorithm Solved Example 1 In this tutorial, we will understand how to apply Classification And Regression Trees (CART) decision tree algorithm to construct and find the optimal decision tree for the given Play Tennis Data. Also, predict the class label for the given example…? Outlook Temp Humidity Windy Play Sunny Hot
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How to find the Entropy – Decision Tree Learning – Machine Learning In this tutorial we will understand, how to find the entropy given the four probabilities p1=0.1, p2=0.2, p3=0.3 and p4=0.4 in the decision tree. Solution: We know that the equation to find Entropy is, Entropy = -∑pi * log2(pi) We were give
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Artificial Intelligence and Machine Learning Tutorial with Simple Solved Examples Introduction Machine Learning In this section, you will learn, Basic Concepts of machine learning such as, Concept Learning, what is a consistent hypothesis, list-then-eliminate algorithm, Find-S algorithm, Candidate elimination algorithm. Concept Learning in Machine Learning Find-S Algorithm Machine Learning and Unanswered Questions of Find-S Algorithm
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Backpropagation Algorithm – Machine Learning – Artificial Neural Network In this tutorial i will discuss the Backpropagation Algorithm and its implementation in Python. Video Tutorial on Backpropagation Algorithm BACKPROPAGATION (training_example, ƞ, nin, nout, nhidden) Each training example is a pair of the form (𝑥, 𝑡), where (𝑥) is the vector of network input values, and
Python Program to Implement the Locally Weighted Regression Algorithm Exp. No. 10. Implement the non-parametric Locally Weighted Regression algorithm in Python in order to fit data points. Select the appropriate data set for your experiment and draw graphs. Locally Weighted Regression Algorithm Regression: Regression is a technique from statistics that are used to predict values
Python Program to Implement the k-Nearest Neighbour Algorithm Exp. No. 9. 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. K-Nearest Neighbor Algorithm Training algorithm: For each training example (x, f (x)), add the
Python Program to Implement the K-Means and Estimation & MAximization Algorithm Exp. No. 8. Apply EM algorithm to cluster a set of data stored in a .CSV file. Use the same data set for clustering using the k-Means algorithm. Compare the results of these two algorithms and comment on the quality of clustering. You can add Java/Python
Python Program to Implement the Bayesian network using pgmpy Exp. No. 7. Write a program to construct a Bayesian network considering medical data. Use this model to demonstrate the diagnosis of heart patients using a standard Heart Disease Data Set. You can use Java/Python ML library classes/API. Theory A Bayesian network is a directed acyclic
Python Program to Implement the Naïve Bayesian Classifier using API for document classification Exp. No. 6. 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
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