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نعم اخي الكريم الاقتران موجود في ال Statistics Toolbox
وهو : COEFF = pcacov(V)[COEFF,latent] = pcacov(V)[COEFF,latent,explained] = pcacov(V)
we sum the absolute factor loadings weighted by the corresponding percentage of explained overall variance. The result is normalized by the sum of variances of all PCs. We call this measure Weighted Average LoaDing Indicator (WALDI). It is computed as defined in Equation 1. المعادلة في الصورة
Where fj is the j-th feature from a set ofFfeatures and the ci are the C principal components. The variance of the i-th PC is denoted by σ2(ci). The factor loading matrix L is a RCxF matrix with C columns and F rows.
The WALDI of a feature is a measure of its information content in terms of orthogonal variances in the data. This value is proportional to the expressiveness of a feature. However, it does not contain information about redundancies among different features. This information can be derived from the factor loading matrix. اريد كيف احل المعادلة تعبت وانا احاول فيها
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