Home learning and automation

Now that in the previous section we have understood how the learning works, it's time to use this concept to make a robot that will automatically understand how we function and make decisions. Based on our decisions, the system will judge what should be done. But this time, rather than giving a set of data by the user, let's make this program create the data for itself. Once the data seems sufficient for itself to function. So, without much explanation, let's get right into it: 

import Adafruit_DHT
import datetime
import RPi.GPIO as GPIO
import time
import numpy as np
import pandas as pd
from sklearn.neighbors import KNeighborsClassifier

GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)

light = 22
fan = 23
sw1 = 13
sw2 = 14

GPIO.setup(light,GPIO.OUT)
GPIO.setup(fan,GPIO.OUT)
GPIO.setup(sw1,GPIO.IN)
GPIO.setup(sw2,GPIO.IN)


sensor = 11
pin = 2


f = open("dataset.csv","a+")
count = 0

while count < 200:

        data = ""

        H = datetime.datetime.now...