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Topic: R programming Assignment -
In this assignment you will use the lda algorithm from the MASS package, the knn algorithm from the class package, and the glm function for logistic regression in R to classify malignant vs. benign breast tumors. The dataset you will use can be found at the UCI Machine Learning Repository, and is labeled Breast Cancer Wisconsin (Diagnostic).
This dataset contains the ID, diagnosis, and 30 real-valued input features. You are to split the dataset into two pieces: a training set consisting of the first 75% of the observations, and a test set consisting of the remaining observations.
Please use your best judgement to preprocess your data appropriately and employ all three algoriths lda, knn, and glm to predict the correct diagnosis for as many test instances as possible. Report your findings along with a written explanation of your process and results. Note, be sure to compare and constrast your results employing each algorithm.
Verified Expert
This task deals with breast cancer data. The study mainly uses three important algorithms to lda, knn, and glm to predict the correct diagnosis for as many test instances as possible. The Naïve Bayes algorithm is used to handle the numeric discretization in many situations. Bayes theorem uses the concept of Naïve Bayes which relates ni (total number of times the word i present in the document) to Pi (the probable chance of getting that event) and E is the last case and H the class
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