[WIP]add the confidence interval computation - #387

this is currently the implementation of ratio modeling for feature selection of random effect in photon.
I follow the algorithm described in the original publication but some twists are made according to discussion with yiming and alex.

• Unit tests all pass.

• Integration tests all pass.

The algorithm in reality(highly related with codebase instead of only mathematical expression) is as follows:

1.pass in the featureStatisticSummary
2.identify the binomial columns
3.compute the lowerbound for binomial columns based on the t value
4.select the feature based on only the following lowerbound criterion(non-binomial and intercept columns are kept automatically)

if (t < 1) {
  T_l = 1 / T_u
}

if (T_l > 1D) {
  //  select feature
}

As a WIP commit, there are things to polish in near future since we currently focus on the feasibility of this experimental method and try to minimize user-side changes :

• unit tests not fully covering all scenarios of feature selection. Currently the binomial cases are not selected, we need to craft some data that covering all cases.

• binomial feature column identification predicate needs to be stronger. Current solution is inherently flawed, we need more computation at feature summary stage to ensure this one.

• hyperparameter interface design. for convenience purposes, the user side interface for pass in normal distribution quartile and lowerbound threshold hyperparameter redesign.

• the relationship with pearson correlation feature selection. We need another parameter to decide on the algorithm of feature selection or mix them in later stage.

• crafted test data need some change, currently some unneeded feature summary entries are not carefully addressed.

• further experiment report and benchmark report after regression tests

• the way we currently keep non-binary and intercept columns is not good for further feature ranking report planned. need redesign

@joshvfleming @ashelkovnykov