Train an ID3 decision tree for a dataset shown in the following table. The table contains 2 categorical attributes (refund and marital status) and 1 continuous attribute (taxable income). Once you got the model then use it to classify the input X1 (No, Single, 95K) and X2 (Yes, Divorced, 120K)

Q: Given the dataset of cars with their mileage and cost for cost prediction: Build a decision tree…

A: I have successfully built the decisiontree. See in the below steps. The reason we used decision tree…

Q: Q.6 Explain impurity measures in decision tree.

A:

Q: Computing as a discipline Difference between Regression Trees and Classification Trees When using…

A: Machine learning which refers to the one it is a subfield of artificial intelligence, which is…

Q: АРРEARS-IN(actor-naтe,age,sex, movie- Q3: title, year, director, studio,budget,salary) and the…

A: Answer:-

Q: Data is often segmented using decision trees, with each branch splitting the data set in half or…

A: The answer is given in the below step

Q: - The overall entropy is (round to 2 decimals): - The information gain for attribute A is (round to…

A: The purpose of machine learning models and Data Scientists in general is to minimize uncertainty,…

Q: Develop a CART model using the test data set that utilizes the same target and predictor variables.…

A: Cart Model: Essentials of Decision Tree:- The decision tree method is a powerful and popular method…

Q: (a)  Run the regression hrsempit = β0 + β1 grant it + β21( year = 1988) + β3Ei + uit where Ei is a…

A: (a) D-i-D regression with treatment indicator:

Q: XOR function mappings can easily be classified by decision trees. True False

A: The answer is

Q: Select all that is true. G has 6 edges G has 6 vertices G is an undirected graph OG contains loops

A: An adjacency matrix is a square matrix used to represent a finite graph. The elements of the matrix…

Q: Task 1: For the training set given below, predict the classification of the following sample X =…

A: Simple Naive bayes classifier I will consider to classify the given data.   Naive bayes classifier :…

Q: Name Smoking Weight hypertension A Yes Overweight Yes B Yes Underweight No C No Underweight No D…

A: Below is the complete solution with explanation in detail for the given question about Decision Tree…

Q: . How many decision trees are there with 3 binary attributes? With 4? . In class we looked at an…

A: 1.  Decision trees are there with 3 binary attributes:-------------For three attributes there are 7…

Temporal difference learning

Temporal difference learning (TD learning) is a concept in machine learning that attributes to a class of model-free reinforcement learning methods. The technique predicts a reward or quantity depending on the future values of the value function.