wpm

import pandas

"""
Join an arbitrary number of data frames, using a multi-index label for each data frame.

For example say you have three data frames each of which lists the classroom and
number of students a teacher has in a given period.

        Classroom  Students
Teacher

wpm

var Promise = require('bluebird');

/**
 * Periodically poll a signal function until either it returns true or a timeout is reached.
 *
 * @param signal function that returns true when the polled operation is complete
 * @param interval time interval between polls in milliseconds
 * @param timeout period of time before giving up on polling
 * @returns true if the signal function returned true, false if the operation timed out
 */

wpm

from pyspark import SparkContext

import numpy as np

from sklearn.cross_validation import train_test_split, Bootstrap
from sklearn.datasets import make_classification
from sklearn.metrics import accuracy_score
from sklearn.tree import DecisionTreeClassifier

def run(sc):

wpm

package wpmcn.structure;

import org.apache.commons.lang.StringUtils;
import org.apache.hadoop.io.ArrayWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.WritableComparable;

import java.util.*;

/**