WEEK 9 - Write a program to implement SVM algorithm to classify the iris data set. Print both correct and wrong predictions.

 WEEK 9 - Write a program to implement SVM algorithm to classify the iris data set. Print both correct and wrong predictions.

WEEK 8: Write a program to implement k-Nearest Neighbors algorithm to classify the iris data set. Print both correct and wrong predictions.

 WEEK 8: Write a program to implement k-Nearest Neighbors algorithm to classify the iris data set. Print both correct and wrong predictions.

K-Nearest Neighbor Algorithm

Training algorithm:

 

·       For each training example (x, f (x)), add the example to the list training examples Classification algorithm:

o   Given a query instance xq to be classified,

§  Let x1 . . .xk denote the k instances from training examples that are nearest to xq

§  Return

Where, f(x_i) function to calculate the mean value of the k nearest training examples.

 

Data Set:

Iris Plants Dataset: Dataset contains 150 instances (50 in each of three classes) 

WEEK 4: • Write a program to demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample.

WEEK 4: • Write a program to demonstrate the working of the decision tree based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample.