Supervised Learning - Classification Week 8 Challenge

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Ans 1 The simplest way to find similarity between two categorical attributes is to assign a similarity of 1 if the values are identical and a similarity of 0 if the values are not identical.

Ans 1 in Attachment Ans 2       Pros K-NN is pretty intuitive and simple: K-NN algorithm is very simple to understand and equally easy to implement. To classify the new data point K-NN algorithm reads through whole dataset to find out K nearest neighbors. K-NN has no assumptions: K-NN is a non-parametric algorithm which…

Ans 1 Pros: It works really well with a clear margin of separation It is effective in high dimensional spaces. It is effective in cases where the number of dimensions is greater than the number of samples. It uses a subset of training points in the decision function (called support vectors), so it is also memory efficient.…

Ans 1 A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. Neural networks can adapt to changing…

Week 2 Challenge Ans 1 First businness moment  =  1.4 Second Business Moment  =  2.326 Third Business Moment  = 0.4086 Fourth Business Moment  =  -30.7919  Ans 2 To calculate mean we sum up all the values and divide the sum with the count of values. This also can be said like , we…

  Ans 1 in the attachment Ans 2 L1 tends to shrink coefficients to zero whereas L2 tends to shrink coefficients evenly. L1 is therefore useful for feature selection, as we can drop any variables associated with coefficients that go to zero. L2, on the other hand, is useful when you have collinear/codependent features.…

Ans 1   Population variance refers to the value of variance that is calculated from population data, and sample variance is the variance calculated from sample data. Due to this value of denominator in the formula for variance in case of sample data is 'n-1', and it is 'n' for population data. Ans 2   In…