Quick Start Guide for Framework3¶

This guide will help you get started with Framework3, demonstrating its basic usage and core concepts.

1. Installation¶

Install Framework3 using pip:

pip install framework3

2. Basic Concepts¶

Framework3 is built around:
- Pipelines: Orchestrate the flow of data through processing steps.
- Filters: Perform specific operations on data.
- Metrics: Evaluate model performance.

3. Creating Your First Pipeline¶

Let's create a simple pipeline that preprocesses data and performs classification:

from framework3 import ClassifierSVMPlugin, F3Pipeline
from framework3.plugins.filters import StandardScalerPlugin
from framework3.plugins.metrics import F1
from framework3.base import XYData
from sklearn.datasets import load_iris

# Load and prepare data
iris = load_iris()
X, y = iris.data, iris.target # type: ignore

# Split the data into training and test sets

X_train, X_test, y_train, y_test = XYData("Iris", "/dataset", [])\
    .train_test_split(X, y, test_size=0.2, random_state=42)

# Make predictions and evaluate
pipeline = F3Pipeline(
    filters=[
        StandardScalerPlugin(),
        ClassifierSVMPlugin()
    ],
    metrics=[F1()]
)
pipeline.fit(X_train, y_train)
predictions = pipeline.predict(X_test)
evaluation = pipeline.evaluate(X_test, y_test, predictions)

Next Steps¶

For more advanced usage and detailed API documentation, refer to:

Happy coding with Framework3!