add visu to prediction regression
This commit is contained in:
@@ -1,6 +1,8 @@
|
||||
import streamlit as st
|
||||
from sklearn.linear_model import LinearRegression
|
||||
import pandas as pd
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
st.header("Prediction: Regression")
|
||||
|
||||
@@ -25,5 +27,34 @@ if "data" in st.session_state:
|
||||
prediction = model.predict(pd.DataFrame([pred_values], columns=data_name))
|
||||
|
||||
st.write("Prediction:", prediction[0])
|
||||
|
||||
fig = plt.figure()
|
||||
dataframe_sorted = pd.concat([X, y], axis=1).sort_values(by=data_name)
|
||||
|
||||
if len(data_name) == 1:
|
||||
X = dataframe_sorted[data_name[0]]
|
||||
y = dataframe_sorted[target_name]
|
||||
|
||||
prediction_array_y = [
|
||||
model.predict(pd.DataFrame([[dataframe_sorted[data_name[0]].iloc[i]]], columns=data_name))[0]
|
||||
for i in range(dataframe_sorted.shape[0])
|
||||
]
|
||||
|
||||
plt.scatter(dataframe_sorted[data_name[0]], dataframe_sorted[target_name], color='b')
|
||||
plt.scatter(dataframe_sorted[data_name[0]], prediction_array_y, color='r')
|
||||
else:
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
|
||||
prediction_array_y = [
|
||||
model.predict(pd.DataFrame([[dataframe_sorted[data_name[0]].iloc[i], dataframe_sorted[data_name[1]].iloc[i]]], columns=data_name))[0]
|
||||
for i in range(dataframe_sorted.shape[0])
|
||||
]
|
||||
|
||||
ax.scatter(dataframe_sorted[data_name[0]], dataframe_sorted[data_name[1]], dataframe_sorted[target_name], color='b')
|
||||
ax.scatter(dataframe_sorted[data_name[0]], dataframe_sorted[data_name[1]], prediction_array_y, color='r')
|
||||
|
||||
st.pyplot(fig)
|
||||
|
||||
|
||||
else:
|
||||
st.error("File not loaded")
|
||||
|
Reference in New Issue
Block a user