# Questions tagged [logarithmic]

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### Standard Scaling After Log Transformation

I have a quick question about whether or not to standardize features after a log transformation. I have one feature that is heavily skewed and requires the log transformation, for the other features I'...
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### Why does the application of the logarithmic function improve the outcome of Random forests?

I have a Random forest model that tries to predict what kind of a useful activity a machine is doing based on its power readings. There are 5 features in a single reading. There are two main types of ...
• 21
1 vote
48 views

### name of log(n+1) plot

I am trying to plot a distribution of positive integers which contains a lot of variance. I opted to use the log of the y-values but that causes issues due to the inclusion of zeros. I though of ...
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1 vote
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### Understanding log odds equation with multiple variables

"If we take the antilog of the regression coefficient associated with obesity, exp(0.415) = 1.52 we get the odds ratio adjusted for age. The odds of developing CVD are 1.52 times higher among ...
• 307
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### How can a log transformation decrease performance?

I'm working on a Demand Forecasting project, I have a lot of 0 (75% of the database) I got a highly right skewed target (5.5). So I decided to log transform my target: target = log(target + 1) When I ...
1 vote
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### Get result from log transformed variable

I can't find some documentation. I had right-skewed target (sale price) variable and also some skewed features at the same way. I did log transformation and fit the regression model and it doing well. ...
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### Effect of log odds on skewed data

Does taking the log of odds bring linearity between the odds of the dependent variable & the independent variables by removing skewness in the data? Is this one reason why we use log of odds in ...
• 307
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### Log odds understanding

Here is my understanding of one reason why we prefer log odds over odds & probability. Please let me know if I got it right. Reasons why we choose log-odds- The range of probability values: $[0,1]$...
• 307
255 views

### Interpretation of Log Odds in Logistic Regression

$\log(\text{odds}) = \text{logit}(P)=ln \big({{P}\over{1-P}}\big)$ $ln\big({{P}\over{1-P}}\big)=\beta_0+\beta_1x$ Consider this example: $0.7=\beta_o+\beta_1(x)+\beta_2(y)+\beta_3(z)$ How can this ...
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1 vote
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### How to justify logarithmically scaled frequency for tf in tf-idf?

I am studying tf-idf (term frequency - inverse document frequency). The original logic for tf was straightforward: count of term t / number of total terms in the document. However, I came across the ...
36 views

### Impact of log transformation and Normalisation in the context of EDA and ML

Is data normalisation an alternative for log transformation? I understand that both helps us to normalisation helps me to make my distribution gaussian. Thanks in advance for your help!
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### XGBoost non-linear regression

Is it possible to use XGBoost regressor to do non-linear regressions? I know of the objectives linear and logistic. The ...
• 151
1 vote
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### RANSAC and R2, why the r2 score is negative?

I was experimenting with curve_fit, RANSAC and stuff trying to learn the basics and there is one thing I don´t understand. Why is R2 score negative here? ...
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