I am trying to create one Machine Learning model using LinearRegression model but I am getting the below error

Question

 training data (input and output) for Measuring temperature using crickets

x_train =[44.000,46.400,43.600,35.000,35.000,32.600,28.900,27.700,25.500,20.375,12.500,37.000,37.500,36.500,36.200] #Cricket Chirp per 1

y_train =[80.500,78.500,78.000,73.500,70.500,68.000,66.000,65.000,61.500,57.000,55.000,76.250,74.000,74.000,72.500]  # Temp in F

 Training based on training data (input and output) for Measuring temperature using crickets

x=x_train

y=y_train

opt = np.polyfit(x, y, 1)

y_pred = int(opt[0]) * x + opt[1]

opt_rmse = math.sqrt(metrics.mean_squared_error(y_pred, y))

slope = opt[0]

bias = opt[1]

#print("y_pred", y_pred, "y ", y)

print("Optimal Training RMSE =", opt_rmse, "for solution", opt)

the error is

ValueError: Found input variables with inconsistent numbers of samples: [0, 15]