Log transformation is effective for handling skewed numerical data, as it compresses large values and stretches smaller ones, reducing skewness and stabilizing variance. It ensures the data conforms to normality, which many statistical methods and machine learning algorithms assume. Transformations like square root or cube root are alternative options for specific distributions. Why Other Options Are Wrong : B) One-hot encoding is for categorical data, not numerical skewness. C) Normalization rescales data but doesn’t address skewness effectively. D) Replacing outliers addresses extreme values but doesn’t fix overall skewness. E) Removing skewed columns discards valuable information and reduces dataset size.
Which of the following laws is/are subsumed by the Code on Social Security, 2020?
I. Employees Provident Fun...
According to “Payment of gratuity Act 2018 (Amendment)” what is maximum amount of gratuity is?
The distance between the pole and centre of curvature of a spherical mirror, in terms of its focal length f, is equal to:
The pluralist perspective assumes that:
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3. Demand draft
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GoI to Launch New Coin of Rs. ______ to Mark New Parliament Inauguration.