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Created 3 years ago
Online property companies offer valuations of houses using machine learning techniques.
The dataset consisted of historic data of houses sold between May 2014 to May 2015.
We will predict the sales of houses in King County with an accuracy of at least 75-80% and understand which factors are responsible for higher property value - $650K and above.”
Problem statementThe aim of this report is to predict the house sales in King County, Washington State, USA using different models (Adaboost & GBM)
STEP 1: IMPORTING LIBRARIES
import numpy as np
import pandas as pd
# import xgboost
import math
import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
from __future__ import division
from scipy.stats import pearsonr
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
#from sklearn.cross_validation import ShuffleSplit
from sklearn.metrics import explained_variance_score
from time import time
from sklearn.metrics import r2_score
import os
from sklearn.model_selection import train_test_split
#from sklearn import cross_validation, tree, linear_model
data = pd.read_csv('kc_house_data.csv')