Version 0.1.2

• RPCA Noisy now has separate fit and transform methods, allowing to impute efficiently new data without retraining
• The class ImputerRPCA has been splitted between a class ImputerRpcaNoisy, which can fit then transform, and a class ImputerRpcaPcp which can only fit_transform
• The class SoftImpute has been recoded to better fit the architecture, and is more tested
• The class RPCANoisy now relies on sparse matrices for H, speeding it up for large instances