2018年4月14日 · The following plot shows coefficients obtained with linear regression (with mpg as the target variable and all others as predictors). For mtcars dataset (here and here) both …

2019年7月31日 · If you choose a linear scale your parameter values will be uniformly selected form $[0,10^4]$. It will be very unlikely that you will small parameter values smaller than $10^{ …

2020年8月21日 · $\begingroup$ @SubhashC.Davar from Wikipedia: "normalization can have a range of meanings.[1] In the simplest cases, normalization of ratings means adjusting values …

2022年10月4日 · According to my understanding, we need feature scaling in linear regression when we use Stochastic gradient descent as a solver algorithm, as feature scaling will help in …

2017年8月8日 · Generally, in tree-based models the scale of the features does not matter. This is because at each tree level, the score of a possible split will be equal whether the respective …

2023年2月28日 · In background literature, I found the use of MEL spectrograms also for bats, and learnt that MEL spectrograms compress the range into log-scale. But if so, I would expect …

2020年7月16日 · However, even though the model achieved reasonable accuracy I was warned that the model did not converge and that I should increase the maximum number of iterations …

2019年1月15日 · I have encoded categorical variables to numerical values. As we know that for feeding values to Linear Algorithms like SVM or KNN, we scale the values for columns having …

2021年2月18日 · $\begingroup$ Thanks. That was so helpful. I have a question, you know by normalization the pred scale is between 0 and 1. now, how could I transfer this scale to the …

The reason is that many linear models, such as the logistic regression and SVM, [...] initialize the weights to 0 or small random values close to 0. Using standardization, we center the feature …