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### Description
Spearman-Brown coefficient
### Purpose
New split-half reliability coefficient
### Use-case
Especially useful in contexts where scales have only two items
### Is your feature req…
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## 🚀 Feature
We can provide a weight Tensor to the regression coefficients, such as pearson, spearman, and r2_score
### Motivation
It should be relatively simple to add weights to these compu…
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-r|--pearsonCorrelation minimum of Pearson’s correlation coefficient between the two adjacent non-overlapping windows
0.5 for sample size (0, 30]
0…
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The column consists of "estimate", "statistic" and "correlation" among others. What do the former mean really?
For example, an X-gene is being unregulated at level of mRNA, then the TF regulating th…
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## Describe the task
So far I have made a correlation matrix for the CEJST thresholds and have begun the process of collapsing thresholds by category.
* correlation matrix:
 used this data set to determine whether individual typists were sensitive to letter, bigram, and trigram frequency. For each typists they measured, mean IKSI for each letter, big…
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When developing code to visualize the cross-correlation between synthetically generated heads based on actual rainfall, I noticed that pastas CCF function does not produce correlations that match the …
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Another metric is the squared correlation, which is simply the square of the Pearson correlation coefficient between the allele dosage of the true genotypes and the allele dosage of the imputed genoty…
szhan updated
2 years ago
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### Environment Details
Please indicate the following details about the environment in which you found the bug:
* SDMetrics version: 0.10 and below
* Python version: Any
* Operating System: An…
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The first step in the process of finding and selecting the most useful features in a dataset, is finding the unimportant features and remove them from dataset to increase training speed and model inte…