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hugo.pradier2
2024-06-21 14:51:06 +02:00
parent 2d1c867bed
commit 089cc66042
2 changed files with 4 additions and 2 deletions
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3
frontend/pages/prediction_classification.py
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@@ -3,6 +3,7 @@ from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score from sklearn.metrics import accuracy_score
from sklearn.preprocessing import LabelEncoder from sklearn.preprocessing import LabelEncoder
import pandas as pd
st.header("Prediction: Classification") st.header("Prediction: Classification")
@@ -53,7 +54,7 @@ if "data" in st.session_state:
value = st.number_input(f"Value for {feature}", value=0.0) value = st.number_input(f"Value for {feature}", value=0.0)
pred_values.append(value) pred_values.append(value)
prediction = model.predict([pred_values]) prediction = model.predict(pd.DataFrame([pred_values], columns=data_name))
if target_name in label_encoders: if target_name in label_encoders:
prediction = label_encoders[target_name].inverse_transform(prediction) prediction = label_encoders[target_name].inverse_transform(prediction)

3
frontend/pages/prediction_regression.py
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@@ -1,5 +1,6 @@
import streamlit as st import streamlit as st
from sklearn.linear_model import LinearRegression from sklearn.linear_model import LinearRegression
import pandas as pd
st.header("Prediction: Regression") st.header("Prediction: Regression")
@@ -21,7 +22,7 @@ if "data" in st.session_state:
st.subheader("Enter values for prediction") st.subheader("Enter values for prediction")
pred_values = [st.number_input(f"Value for {feature}", value=0.0) for feature in data_name] pred_values = [st.number_input(f"Value for {feature}", value=0.0) for feature in data_name]
prediction = model.predict([pred_values]) prediction = model.predict(pd.DataFrame([pred_values], columns=data_name))
st.write("Prediction:", prediction[0]) st.write("Prediction:", prediction[0])
else: else: