PREDICTIVE MODELING

A predictive analysis generates a predictive model (Padj(Y|X)) based on two separate pieces of information, The predictive analysis begins by generating a base model distribution (Pgen(Y|X)) from the original training data set (Dorig) containing tuples (x,y) of indicators (x) and corresponding labels (y). Using the “true” distribution (Ptrue(X)) of indicators, a random data set (D′) of indicator records (x) is generated reflecting this “true” distribution (Ptrue(X)). Subsequently, the base model (Pgen(Y|X)) is applied to said random data set (D′), thus assigning a label (y) or a distribution of labels to each indicator record (x) in said random data set (D′) and generating an adjusted training set (Dadj). Finally, an adjusted predictive model (Padj(Y|X)) is trained based on said adjusted training set (Dadj).