The best way is to use Bayesian parametric classification framework.

attentive

This can be done in the Eidos system. Below is a brief information about the method of ask-analysis and Eidos system.

THEORETICAL FOUNDATIONS, TECHNOLOGY AND TOOLS

AUTOMATED SYSTEM-COGNITIVE ANALYSIS

(theory and method of quantitative detection in a comparable form of force and direction of cause-and-effect dependences in incomplete noisy data of very large dimension of numerical and non-numerical nature, measured in different types of scales and units of measurement)

This section is about the ask-the analysis and the system "EIDOS-X++"

There are many artificial intelligence systems. Universal cognitive analytical system "Eidos-x++" differs from them in the following parameters:

- developed in a universal setting, independent of the subject area. Therefore, it is universal and can be applied in many subject areas (http://lc.kubagro.ru/aidos/index.htm);

- is in full open free access (http://lc.kubagro.ru/aidos/_Aidos-X.htm), and with relevant source texts (http://lc.kubagro.ru/__AIDOS-X.txt);

- is one of the first domestic systems of artificial intelligence of the personal level, i.e. it does not require special training from the user in the field of artificial intelligence technologies (there is an act of introduction of the "Eidos" system of 1987) (http://lc.kubagro.ru/aidos/aidos02/PR-4.htm);

- provides stable detection in a comparable form of force and direction of cause-and-effect dependencies in incomplete noisy interdependent (nonlinear) data of very large dimension of numerical and non-numerical nature, measured in different types of scales (nominal, ordinal and numerical) and in different units of measurement (i.e. does not impose strict requirements on the data that can not be performed, and processes the data that is);

- contains a large number of local (supplied with the installation) and cloud-based educational and scientific applications (currently about 30 and 132, respectively) (http://lc.kubagro.ru/aidos/Presentation_Aidos-online.pdf);

- provides multi-language interface support in 44 languages. Language databases are included in the installation and can be replenished automatically;

- supports on-line learning environment and is widely used all over the world (http://aidos.byethost5.com/map3.php);

- provides conversion of initial empirical data into information, and its knowledge and solution using this knowledge of classification problems, decision support and research of the subject area by studying its system-cognitive model, while generating a very large number of tabular and graphical output forms (development of cognitive graphics), many of which have no analogues in other systems (examples of forms can be found in: http://lc.kubagro.ru/aidos/aidos18_LLS/aidos18_LLS.pdf)

You can try with and Ensemble model, obtaining a weighted result for each model.

I think it is better to use any one of the non-linear classifier for your case. Best of my knowledge, it is better to use deep Bayes back-propagation, quadratic classifier, etc.