appliances = ["hvac", "fridge", "wm", "dw", "ec", "mw", "oven", "wh"] features = ["Static", "Monthly+Static", "Monthly"] appliances = ['fridge,"hvac'] import sys CLUSTER = True if CLUSTER: sys.path.insert(0, '/if6/nb2cz/anaconda/lib/python2.7/site-packages') sys.path.insert(0, '../code') import numpy as np import pandas as pd from create_df_larger import read_df_larger df, dfc, all_homes, appliance_min, national_average = read_df_larger() df = df.rename( columns={ 'house_num_rooms': 'num_rooms', 'num_occupants': 'total_occupants', 'difference_ratio_min_max': 'ratio_difference_min_max' }) K_min, K_max = 1, 3 F_min, F_max = 1, 8 from all_functions import * from features_larger import * SLURM_OUT = "../slurm_out" from subprocess import Popen
# NEED TO RUN ON CLUSTER import sys CLUSTER=True if CLUSTER: sys.path.insert(0, '/if6/nb2cz/anaconda/lib/python2.7/site-packages') import os import numpy as np import pandas as pd from create_df_larger import read_df_larger df, dfc, all_homes, appliance_min, national_average = read_df_larger() df = df.rename(columns={'house_num_rooms':'num_rooms', 'num_occupants':'total_occupants', 'difference_ratio_min_max':'ratio_difference_min_max'}) K_min, K_max = 1,6 F_min, F_max=1,8 from all_functions import * from features_larger import * import sys from sklearn.neighbors import KNeighborsRegressor from sklearn.cross_validation import ShuffleSplit from sklearn.cross_validation import LeaveOneOut NUM_NEIGHBOUR_MAX = 6