Dev aiscool

Port of this python code in Javascript.

LSH from Wikipedia:

Locality-sensitive hashing (LSH) reduces the dimensionality of high-dimensional data. LSH hashes input items so that similar items map to the same “buckets” with high probability (the number of buckets being much smaller than the universe of possible input items). LSH differs from conventional and cryptographic hash functions because it aims to maximize the probability of a “collision” for similar items. Locality-sensitive hashing has much in common with data clustering and nearest neighbor search.

More explanation:

	import pandas as pd
	from sklearn.metrics import accuracy_score
	from sklearn.neural_network import MLPClassifier

	df = pd.read_csv('Baseline.csv') #Baseline.csv dengan full.csv
	maxi = 0
	max_i = 0
	max_j = 0
	for i in range(10):
	data = df.sample(frac=0.7, random_state=i)

	#!/usr/bin/env python

	"""
	Original Script : https://gist.github.com/efaisal/4583986

	Muat turun data waktu solat Jakim

	Create database nama 'waktusolat' dalam MySQL

	Lepas tu create table 'waktu_solat'

	import matplotlib.pyplot as plt
	from sklearn import svm,metrics
	import pandas as pd

	df = pd.read_csv('training-test.csv')
	df = df.iloc[:,1:]

	train = df.sample(frac=0.9, random_state=255)
	test = df.drop(train.index)


	package javaapplication1;

	/**
	*
	* @author commander
	*/

	import java.io.BufferedReader;
	import java.io.FileNotFoundException;

	//source : http://www.codebytes.in/2015/02/a-shortest-path-finding-algorithm.html
	import java.util.*;

	public class AStar {
	public static final int V_H_COST = 1;

	static class Cell{
	int heuristicCost = 0; //Heuristic cost
	int finalCost = 0; //G+H
	int i, j;