-- Oct 11 In-Class Exercise
Hypothesis 1 - SVM converges to a more accurate model when the amount of training data increases.
Testing - This hypothesis can be tested by increasing the amount of training data and comparing the accuracy.
Hypothesis 2 - Complex shapes require more training data as compared to simple shapes to get an accurate model.
Testing - This hypothesis can be tested by comparing the accuracy and no. of training samples used for different shapes.
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Edited: 2017-10-11)
Hypothesis 1 - SVM converges to a more accurate model when the amount of training data increases.
Testing - This hypothesis can be tested by increasing the amount of training data and comparing the accuracy.
Hypothesis 2 - Complex shapes require more training data as compared to simple shapes to get an accurate model.
Testing - This hypothesis can be tested by comparing the accuracy and no. of training samples used for different shapes.