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Data MiningFor the following vectors, \mathbf{x} and \mathbf{y}, calculate the indicated similarity or distance measures : (i) \mathbf{x} = (0, -1, 0, 1), \mathbf{y} = (1, 0, -1, 0) cosine, correlation (ii) \mathbf{x} = (0, 1, 0, 1), \mathbf{y} = (1, 0, 1, 0) Euclidean, SMC20227mMACHINE LEARNINGGiven a dataset with two features: X = [[2, 0], [0, 1], [0, 2]]. Compute the covariance matrix, eigenvalues, and the principal components.20257mData MiningThe 0 (zero) correlation value between two data object indicates (i) no linear relationship between two objects (ii) non-linear relationship between two objects (iii) linear relationship between two objects (iv) Both (i) and (ii)20222mData MiningJaccard coefficient is frequently used to handle objects consisting of (i) symmetric binary attribute (ii) asymmetric binary attribute (iii) Both (i) and (ii) (iv) None of the above20222m
PreviousWhat do you mean by under-fitting and over-fitting of a classification model?NextBuild a decision tree using the training data in the table given below. Divide the height attribute into ranges as follows : \{0, 1.6\], (1.6, 1.7\], (1.7, 1.8\], (1.8, 1.9\], (1.9, 2.0\], (2.0, 5.0\] | Gender | Height (m) | Class | |:---:|:---:|:---:| | F | 1.6 | Short | | M | 2 | Tall | | F | 1.9 | Medium | | F | 1.88 | Medium | | F | 1.7 | Short | | M | 1.85 | Medium | | F | 1.6 | Short | | M | 1.7 | Short | | M | 2.2 | Tall | | M | 2.1 | Tall | | F | 1.8 | Medium | | M | 1.95 | Medium | | F | 1.9 | Medium | | F | 1.8 | Medium | | F | 1.75 | Medium |