Alexey Korchevsky mitallast

![alt](http://latex.codecogs.com/gif.latex? \begin{align*} x^2 + y^2 &= 1 \\ y &= \sqrt{1 - x^2} \end{align*} )

	+--------+--------------------+-----+--------------------+--------------------+--------------------+--------------------+----------+
	\|category\| text\|label\| words\| features\| rawPrediction\| probability\|prediction\|
	+--------+--------------------+-----+--------------------+--------------------+--------------------+--------------------+----------+
	\| 3001\|Плойки и наборы V...\| 24.0\|[плойки, и, набор...\|(10000,[326,796,1...\|[-174.67716870697...\|[6.63481663197049...\| 24.0\|
	\| 833\|"Чехол-обложка дл...\| 1.0\|["чехол-обложка, ...\|(10000,[514,986,1...\|[-379.37151502387...\|[5.32678001676623...\| 1.0\|
	\| 833\|"Чехол-обложка дл...\| 1.0\|["чехол-обложка, ...\|(10000,[514,986,1...\|[-379.84825219376...\|[2.15785456821554...\| 1.0\|
	\| 833\|"Чехол-обложка дл...\| 1.0\|["чехол-обложка, ...\|(10000,[290,514,9...\|[-395.42735009477...\|[6.44323423370500...\| 1.0\|
	\| 833\|"Чехол-обложка дл...\| 1.0\|["чехол-обложка, ...\|(10000,[290,514,9...\|[-396.10251348

	+--------+--------------------+-----+--------------------+--------------------+----------+
	\|category\| text\|label\| words\| features\|prediction\|
	+--------+--------------------+-----+--------------------+--------------------+----------+
	\| 0\|"Мышь беспроводна...\| 0.0\|["мышь, беспровод...\|(10000,[372,634,6...\| 3.0\|
	\| 9\|покрышка Данлоп 2...\| 8.0\|[покрышка, данлоп...\|(10000,[118,1828,...\| 0.0\|
	\| 0\|"Стилус для Nokia...\| 0.0\|["стилус, для, no...\|(10000,[45,290,57...\| 1.0\|
	\| 9\|покрышка Континен...\| 8.0\|[покрышка, контин...\|(10000,[50,121,18...\| 0.0\|
	\| 833\|Alcatel OT-890 St...\| 1.0\|[alcatel, ot-890,...\|(10000,[971,1031,...\| 0.0\|
	\| 833\|"Nokia Asha 200 G...\| 1.0\|["nokia, asha, 20...\|(10000,[544,548,1...\| 0.0\|
	\| 833\|"Samsung Champ Ne...\| 1.0\|["samsung, champ,...\|(10000,[182,325,6...\| 0.0\|

	+--------+--------------------+-----+--------------------+--------------------+--------------------+--------------------+----------+
	\|category\| text\|label\| words\| features\| rawPrediction\| probability\|prediction\|
	+--------+--------------------+-----+--------------------+--------------------+--------------------+--------------------+----------+
	\| 833\|"Чехол-обложка дл...\| 1.0\|["чехол-обложка, ...\|(10000,[514,986,1...\|[-379.50617089769...\|[3.15784456725782...\| 1.0\|
	\| 833\|"Чехол-обложка дл...\| 1.0\|["чехол-обложка, ...\|(10000,[290,514,9...\|[-395.54097963559...\|[3.98362185323457...\| 1.0\|
	\| 0\|"Держатель для мо...\| 0.0\|["держатель, для,...\|(10000,[34,45,47,...\|[-333.85171077966...\|[0.88443426309164...\| 0.0\|
	\| 9\|Шина Nordman RS 1...\| 8.0\|[шина, nordman, r...\|(10000,[1124,1223...\|[-70.906588615908...\|[5.01470370003123...\| 8.0\|
	\| 833\|"Набор для зарядк...\| 1.0\|["набор, для, зар...\|(10000,[130,292,5...\|[-530.30719860

	import org.apache.spark.ml.Pipeline
	import org.apache.spark.ml.classification.NaiveBayes
	import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
	import org.apache.spark.ml.feature.{HashingTF, StringIndexer, Tokenizer}
	import org.apache.spark.ml.tuning.{CrossValidator, ParamGridBuilder}
	import org.apache.spark.sql.SQLContext
	import org.apache.spark.{SparkConf, SparkContext}

	object SimpleApp {
	def main(args: Array[String]) {

	from scikits.audiolab import Sndfile
	import numpy as np
	import matplotlib.pyplot as plt
	import scipy.signal

	f = Sndfile('impulse.wav', 'r')
	data = np.array(f.read_frames(f.nframes), dtype=np.float64)
	f.close()

	fs = f.samplerate

	import pandas_datareader.data as web
	import matplotlib.pyplot as plt
	from sklearn.linear_model import LinearRegression
	import numpy as np
	import datetime

	start = datetime.datetime(2010, 1, 1)
	end = datetime.datetime(2015, 3, 8)
	usd = web.DataReader("USD", 'google', start, end)

	$ go test -bench=.
	testing: warning: no tests to run
	PASS
	BenchmarkJsonReflection-8 100000 14689 ns/op
	BenchmarkFFJson-8 200000 6345 ns/op
	ok github.com/mitallast/goprotoserver/protocol 2.974s

	# init

	# L - error function
	def gbm_L(y, z):
	return (y-z)**2

	# derivative of L function without coefficient `2`
	def dbm_L_der(y, z):
	# ignore coefficient 2
	return y - z