incr_mean_variance_axis(X, axis, last_mean, last_var, last_n)¶
Compute incremental mean and variance along an axix on a CSR or CSC matrix.
last_mean, last_var are the statistics computed at the last step by this function. Both must be initialized to 0-arrays of the proper size, i.e. the number of features in X. last_n is the number of samples encountered until now.
- XCSR or CSC sparse matrix, shape (n_samples, n_features)
- axisint (either 0 or 1)
Axis along which the axis should be computed.
- last_meanfloat array with shape (n_features,)
Array of feature-wise means to update with the new data X.
- last_varfloat array with shape (n_features,)
Array of feature-wise var to update with the new data X.
- last_nint with shape (n_features,)
Number of samples seen so far, excluded X.
- meansfloat array with shape (n_features,)
Updated feature-wise means.
- variancesfloat array with shape (n_features,)
Updated feature-wise variances.
- nint with shape (n_features,)
Updated number of seen samples.
NaNs are ignored in the algorithm.