supachaic

import React, { Component } from 'react';
import { Link } from 'react-router-dom';

export default class Home extends Component {
  render() {
    return (
      <div>
        <h2>BNK48 Facial Recognition App</h2>
        <li>
          <Link to="/photo">Photo Input</Link>

supachaic

import React, { Component } from 'react';
import { Route, Router } from 'react-router-dom';
import createHistory from 'history/createBrowserHistory';
import './App.css';

import Home from './views/Home';

class App extends Component {
  render() {
    return (

supachaic

def all_subs(idx_list):
    if idx_list == []:
        return [[]]

    indices = all_subs(idx_list[1:])

    return indices + [[idx_list[0]] + i for i in indices]

def search_combination(predict_list, y_val, score_name):
    idx_list = list(range(len(predict_list)))

supachaic

def vote(estimators, threshold, X_train, y_train, X_val, y_val, X_test, score_name):
    
    predict_list = []
    estimator_list = []
    
    for estimator_name in estimators:  
        try:
            params, val_score, timestamp = get_params(estimator_name)
            if val_score > threshold:
                print('Ensemble add %s' % estimator_name)

supachaic

import scipy.stats as st
from sklearn.model_selection import RandomizedSearchCV
from xgboost import XGBClassifier

# Preconfigure estimator and parameters
estimator = XGBClassifier(nthreads=-1)
params = {  
            "n_estimators": st.randint(3, 40),
            "max_depth": st.randint(3, 40),
            "learning_rate": st.uniform(0.05, 0.4),

supachaic

from sklearn.ensemble import RandomForestClassifier 
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import ExtraTreesClassifier, VotingClassifier
from xgboost import XGBClassifier

rfo = RandomForestClassifier()
ada = AdaBoostClassifier()
ext = ExtraTreesClassifier()
xgb = XGBClassifier()