It's a silly problem, I know, but it's getting my nerves. Everything seems fine, but I cannot get the line to show on the plot.
I've put it in a public Google notebook, for your convenience.
t represents months, and f_t are sales (accumulated). I feed the model 12 months of data, and use the 13th month for prediction. Simple.
import random
import pandas as pd
import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
from matplotlib import pyplot as plt
muestra = []
# creamos las 13 muestras de acuerdo a la fórmula provista en la Situación Problemática.
for i in range(1,14):
t = 3*i + 2*(random.uniform(-1, 1))
muestra.append((i, t))
df = pd.DataFrame(muestra)
df.rename(columns={0:"t", 1:"f_t"}, inplace=True)
train = df.loc[:11]
test = df.loc[12:]
X_train = train.t.values.reshape(-1, 1)
y_train = train.f_t.values
X_test = test.t.values.reshape(-1, 1)
y_test = test.f_t.values
LR_model = LinearRegression()
LR_model.fit(X_train, y_train)
y_pred = LR_model.predict(X_test)
%matplotlib inline
plt.plot(X_test, y_pred, label="Regresión Lineal", color='g')
plt.scatter(X_train, y_train, label="Muestra",color='b')
plt.scatter(X_test, y_test, label="Mes 13",color='r')
plt.legend()
plt.xlabel('Meses (t)')
plt.ylabel('Ventas (f(t))')
plt.title("Análisis en base a la técnica de regresión lineal simple")
plt.show()
Now, I get the scatter points, but not the regression line. What am I missing? Thank you.
