{"library":"orange3","title":"Orange3 Data Mining Framework","description":"Orange3 is a component-based data mining framework for Python, offering visual programming and a rich set of widgets for data preprocessing, modeling, and evaluation. The current stable version is 3.40.0, with a release cadence of approximately 2-3 minor versions per year.","language":"python","status":"active","last_verified":"Sat May 09","install":{"commands":["pip install orange3"],"cli":{"name":"orange-canvas","version":"Traceback (most recent call last):"}},"imports":["from Orange.data import Table","from Orange.preprocess import Normalize, Continuize, Impute","from Orange.evaluation import CrossValidation, scoring"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"from Orange.data import Table\nfrom Orange.preprocess import Normalize\nfrom Orange.classification import RandomForestLearner\nfrom Orange.evaluation import CrossValidation, scoring\n\n# Load dataset (automatically downloads if not present)\ndata = Table('iris')\n\n# Preprocess: normalize features\nnormalizer = Normalize()\ndata_norm = normalizer(data)\n\n# Train a random forest model\nlearner = RandomForestLearner(n_estimators=50, random_state=42)\n\n# Cross-validation\nresults = CrossValidation(data_norm, [learner], k=5)\nprint('CA:', scoring.CA(results)[0])","lang":"python","description":"Loads the Iris dataset, normalizes features, trains a Random Forest, and evaluates with 5-fold cross-validation.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}