markdregan

from probatus.feature_elimination import ShapRFECV, EarlyStoppingShapRFECV
from sklearn.datasets import make_classification
from catboost import CatBoostClassifier
import numpy as np
import pandas as pd


def get_best_idx(shap_report):
    shap_report["eval_metric"] = shap_report["val_metric_mean"]
    best_iteration_idx = shap_report["eval_metric"].argmax()

markdregan

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {

markdregan

markdregan

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Plot posterior predictive distribution from hierarchal model"
   ]
  },
  {

markdregan

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Plot posterior predictive distribution from hierarchal model"
   ]
  },
  {

markdregan

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Plot posterior predictive distribution from hierarchal model"
   ]
  },
  {