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We wish to perform classification of Breast Cancer test samples from a source data set. The dataset consists of 5 6 9 samples with 3
We wish to perform classification of Breast Cancer test samples from a source data set. The
dataset consists of samples with feature measurements per sample. Your job is train on
of the data to see how well it will classify the remaining of the data using a Support
Vector Machine approach. The data points are to be classified into 'Benign' and 'Malignant'
based on the data available.
a From your training set, formulate a linear SVM to perform classification using either the
PCA or FLD dimensionally reduced data. Report on your classification error and your
Type I and Type II errors for cancer detection. You cannot use the MATLAB SVM
functions to perform your training or classification; formulate the problem and use the
optimization toolbox.
b From your training set, formulate a nonlinear SVM to perform classification using either
the PCA or FLD dimensionally reduced data. Report on your classification error and
your Type I and Type II errors for cancer detection. You cannot use the MATLAB SVM
functions to perform your training or classification; formulate the problem and use the
optimization toolbox.
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