Minor improvements
Browse files
app.py
CHANGED
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@@ -5,8 +5,6 @@ import numpy as np
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from sklearn import datasets, linear_model
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from sklearn.metrics import mean_squared_error, r2_score
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from functools import partial
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-
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FIGSIZE = (10,10)
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feature_names = ["age", "body-mass index (BMI)", "blood pressure",
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@@ -33,7 +31,7 @@ def create_dataset(feature_id=2):
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def train_model(input_data):
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# We
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if input_data == 'age':
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feature_id = 0
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else:
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@@ -57,7 +55,7 @@ def train_model(input_data):
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# Plot outputs
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fig = plt.figure(figsize=FIGSIZE)
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plt.title(input_data)
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plt.scatter(diabetes_X_test, diabetes_y_test, color="black")
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plt.plot(diabetes_X_test, diabetes_y_pred, color="blue", linewidth=3)
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@@ -68,7 +66,7 @@ def train_model(input_data):
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return fig, regr.coef_, mse, r2
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title = "Linear Regression Example"
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description = "The example shows how linear regression attempts to draw a straight line that will best minimize the residual sum of squares between the observed responses in the dataset"
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with gr.Blocks() as demo:
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gr.Markdown(f"## {title}")
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@@ -77,7 +75,7 @@ with gr.Blocks() as demo:
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with gr.Column():
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with gr.Row():
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plot = gr.Plot(
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with gr.Column():
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input_data = gr.Dropdown(choices=feature_names, label="Feature", value="body-mass index")
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coef = gr.Textbox(label="Coefficients")
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from sklearn import datasets, linear_model
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from sklearn.metrics import mean_squared_error, r2_score
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FIGSIZE = (10,10)
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feature_names = ["age", "body-mass index (BMI)", "blood pressure",
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def train_model(input_data):
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# We removed the sex variable
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if input_data == 'age':
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feature_id = 0
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else:
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# Plot outputs
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fig = plt.figure(figsize=FIGSIZE)
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# plt.title(input_data)
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plt.scatter(diabetes_X_test, diabetes_y_test, color="black")
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plt.plot(diabetes_X_test, diabetes_y_pred, color="blue", linewidth=3)
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return fig, regr.coef_, mse, r2
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title = "Linear Regression Example 📈"
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description = "The example shows how linear regression attempts to draw a straight line that will best minimize the residual sum of squares between the observed responses in the dataset"
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with gr.Blocks() as demo:
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gr.Markdown(f"## {title}")
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with gr.Column():
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with gr.Row():
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plot = gr.Plot()
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with gr.Column():
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input_data = gr.Dropdown(choices=feature_names, label="Feature", value="body-mass index")
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coef = gr.Textbox(label="Coefficients")
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