cheesinglee

Number of map-reduce blocks on columns, and population size on rows [200,500,1000,5000,10000]

1		3		5		10		20		30		50
================================================================================
uncorrelated data
0.020074	0.067028	0.150469	0.112782	0.260606	0.485714	0.400000
-0.018003	-0.095463	-0.102538	0.050660	0.031538	0.358824	0.333333
-0.011529	-0.000860	-0.019766	-0.164176	-0.203649	-0.167781	-0.183459
-0.004745	-0.021326	-0.014286	-0.075185	-0.091779	-0.063402	-0.051401
0.005333	0.000626	0.007783	0.024034	-0.040481	-0.017537	-0.115995

cheesinglee

#!/usr/bin/env python

from __future__ import print_function
from scipy.stats import pearsonr,spearmanr
"""
Edward Tufte uses this example from Anscombe to show 4 datasets of x
and y that have the same mean, standard deviation, and regression
line, but which are qualitatively different.

matplotlib fun for a rainy day

cheesinglee

Dynamic scatterplot of the iris dataset.

Controls:

• Left click to choose X-axis.
• Right click to choose Y-axis.
• Alt + right click to choose color axis.
• Repeat click (left, right, or alt) for log scale.
• Hover over a point to see all field values.
• Click a multi-point (larger circle) to cycle through values.

cheesinglee

<?xml version="1.0" encoding="UTF-8"?><PMML xmlns="http://www.dmg.org/PMML-4_3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" version="4.3">
  <Header description="Model kind: logistic">
    <Application name="BigML"/>
  </Header>
  <DataDictionary>
    <DataField name="sepal length" displayName="" optype="continuous" dataType="double">
      <Extension name="BigML-Field_ID" value="000000"/>
    </DataField>
    <DataField name="sepal width" displayName="" optype="continuous" dataType="double">
      <Extension name="BigML-Field_ID" value="000001"/>

cheesinglee

# -*- coding: utf-8 -*-
"""
Created on Thu Oct  3 12:24:41 2013

@author: cheesinglee
"""

import praw

from csv import DictWriter

cheesinglee

#!/usr/bin/python

import functools
import numpy as np
from matplotlib import pyplot as pp
from matplotlib.collections import PolyCollection
from matplotlib.cm import get_cmap

from bigml.api import BigML