Classification Exercise Using Logistic OR NaiveBayes - IT Assignment Help

Assignment Task

1. Consider the dataset that you performed comprehensive EDA on. In this assignment you will run four classification exercises:
-- classification exercise using Logistic OR NaiveBayes OR LDA/QDA.
-- Classification exercise using SVM
-- Decision Tree
-- Nearest Neighbor

Determine their performance characteristics (RoC plot,AUC,ConfusionMatrix,Accuracy, Specificity, Precision, Recall (sensitivity), and tabulate them. Discuss in detail the observed differences and the cause for such difference.
Estimate the variance and bias for these algorithms, compare and discuss the observed differences.
Also generate a classification table for each observation as follows
Observation
Given
Class
Algo 1
(predicted Class)
Algo 2
(predicted Class)
Algo 3
(predicted Class)
Algo 4
(predicted Class)

2) Apply any three of the ensemble methods to your dataset and compare ensemble (HW03) performance with individual classifier (HW02) performance. Implement ensemble using parallel and or Spark framework. Showcase your programming skills to help data scientists overcome performance and capacity constraints.
You can pick three out of this list:
CrossValidation,
Leave One out
Bagging
RandomForest
Boosting
Stacking

Determine variance and bias and compare the algorithms bias and variance. What does CV do to bias and variance?

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