I am making a program to predict the x and y value using linear regression.
I can predict y from x. However, when trying to predict x given y i do not get the intended result. Output:
Given (x) predict (y):
x = 10
85.59308314937454
Given (y) predict (x):
y = 85
-45.75349521707133
code:
def place_y(x, slope, intercept):
return slope * x + intercept
def predict_value_x():
"""Using the line of regression a value can be predicted based on a given value.
i.e. Predict the speed of a car (y) given it is (x) years old"""
from scipy import stats
age_x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11, 12, 9, 6] # population
speed_y = [99, 86, 87, 88, 111, 86, 103, 87, 94, 78, 77, 85, 86] # population
slope, intercept, r, p, std_err = stats.linregress(age_x, speed_y) # get stats values
predict_value = int(input("Given (x) predict (y): \nx = ")) # age of car(x)
predicted = place_y(predict_value, slope, intercept) # the speed of car given x
print(predicted)
predict_value_x()
def predict_value_y():
"""Using the line of regression a value can be predicted based on a given value.
i.e. Predict the age of a car (x) given its speed (y)"""
from scipy import stats
age_x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11, 12, 9, 6] # population
speed_y = [99, 86, 87, 88, 111, 86, 103, 87, 94, 78, 77, 85, 86] # population
slope, intercept, r, p, std_err = stats.linregress(age_x, speed_y) # get stats values
predict_value = int(input("Given (y) predict (x): \ny = ")) # age of car(x)
predicted = place_y(predict_value, slope, intercept) # the speed of car given x
print(predicted)
>Solution :
y=ax+b -> x=(y-b)/a
The problem is that you try to solve by y twice.
You need an aditional function that solves by y:
def place_x(y, slope, intercept):
return (y - intercept)/slope
and replace placey in your predict_value_y function:
predicted = place_x(predict_value, slope, intercept)
the entire code could look like:
def place_y(x, slope, intercept):
return slope * x + intercept
def place_x(y, slope, intercept):
return (y - intercept)/slope
def predict_value_x():
"""Using the line of regression a value can be predicted based on a given value.
i.e. Predict the speed of a car (y) given it is (x) years old"""
from scipy import stats
age_x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11, 12, 9, 6] # population
speed_y = [99, 86, 87, 88, 111, 86, 103, 87, 94, 78, 77, 85, 86] # population
slope, intercept, r, p, std_err = stats.linregress(age_x, speed_y) # get stats values
predict_value = int(input("Given (x) predict (y): \nx = ")) # age of car(x)
predicted = place_y(predict_value, slope, intercept) # the speed of car given x
print(predicted)
predict_value_x()
def predict_value_y():
"""Using the line of regression a value can be predicted based on a given value.
i.e. Predict the age of a car (x) given its speed (y)"""
from scipy import stats
age_x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11, 12, 9, 6] # population
speed_y = [99, 86, 87, 88, 111, 86, 103, 87, 94, 78, 77, 85, 86] # population
slope, intercept, r, p, std_err = stats.linregress(age_x, speed_y) # get stats values
predict_value = int(input("Given (y) predict (x): \ny = ")) # age of car(x)
predicted = place_x(predict_value, slope, intercept) # the speed of car given x
print(predicted)
predict_value_y()