padjiman

def lin(params,x):
    return params[0]*x + params[1]

def linear_gradients(params_to_learn,x,y):
    a = params_to_learn[0] 
    b = params_to_learn[1]
    de_da = 2*x*(a*x+b-y)
    de_db = 2*(a*x+b-y)  
    
    return [de_da,de_db]

padjiman

package vw;

import java.io.*;
import java.text.ParseException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.stream.Collectors;

padjiman

vw train.vw -c --passes 4 -f model.vw --loss_function logistic --interactions ci -b 26

padjiman

padjiman

padjiman

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [