{
"name": "data-science/linfa-examples",
"description": "A collection of machine learning examples using Linfa 0.7.1, including classification, regression, and clustering",
"type": "binary",
"files": [
{
"source": "src/main.rs",
"target": "src/main.rs"
},
{
"source": "src/classification.rs",
"target": "src/classification.rs"
},
{
"source": "src/decision_tree.rs",
"target": "src/decision_tree.rs"
},
{
"source": "src/regression.rs",
"target": "src/regression.rs"
},
{
"source": "src/clustering.rs",
"target": "src/clustering.rs"
},
{
"source": "src/data_utils.rs",
"target": "src/data_utils.rs"
},
{
"source": "Cargo.toml.template",
"target": "Cargo.toml"
},
{
"source": "README.md",
"target": "README.md"
},
{
"source": "data/sample_classification.csv",
"target": "data/sample_classification.csv",
"condition": "data_format == \"CSV files\" || data_format == \"All formats (CSV, JSON)\""
},
{
"source": "data/sample_regression.csv",
"target": "data/sample_regression.csv",
"condition": "data_format == \"CSV files\" || data_format == \"All formats (CSV, JSON)\""
},
{
"source": "data/sample_clustering.csv",
"target": "data/sample_clustering.csv",
"condition": "data_format == \"CSV files\" || data_format == \"All formats (CSV, JSON)\""
},
{
"source": "data/sample_classification.json",
"target": "data/sample_classification.json",
"condition": "data_format == \"JSON files\" || data_format == \"All formats (CSV, JSON)\""
},
{
"source": "data/sample_regression.json",
"target": "data/sample_regression.json",
"condition": "data_format == \"JSON files\" || data_format == \"All formats (CSV, JSON)\""
},
{
"source": "data/sample_clustering.json",
"target": "data/sample_clustering.json",
"condition": "data_format == \"JSON files\" || data_format == \"All formats (CSV, JSON)\""
}
],
"dependencies": {
"default": [
"anyhow = \"1.0\"",
"linfa = \"0.7.1\"",
"linfa-linear = \"0.7.1\"",
"linfa-logistic = \"0.7.1\"",
"linfa-trees = \"0.7.1\"",
"linfa-clustering = \"0.7.1\"",
"linfa-datasets = { version = \"0.7.1\", features = [\"generate\"] }",
"ndarray = { version = \"0.15\", features = [\"serde\"] }",
"ndarray-rand = \"0.14\"",
"ndarray-stats = \"0.5\"",
"rand = \"0.8\"",
"rand_xoshiro = \"0.6.0\"",
"csv = \"1.3\"",
"serde = { version = \"1.0\", features = [\"derive\"] }",
"serde_json = \"1.0\""
]
},
"metadata": {
"category": "Machine Learning",
"level": "Intermediate",
"keywords": ["machine-learning", "classification", "regression", "clustering", "linfa"]
},
"prompts": {
"data_source": {
"question": "What type of data source would you like to use for the examples?",
"options": ["Synthetic data (generated)", "Custom data files", "Both (examples will show both options)"],
"default": "Both (examples will show both options)"
},
"data_format": {
"question": "What data format would you like to use?",
"options": ["CSV files", "JSON files", "All formats (CSV, JSON)"],
"default": "CSV files",
"condition": "data_source == \"Custom data files\" || data_source == \"Both (examples will show both options)\""
}
},
"next_steps": [
"🧪 Try LogisticRegression classification: cd {{project_name}} && cargo run -- classification",
"🌲 Try DecisionTree classification: cargo run -- decision_tree",
"📈 Try LinearRegression example: cargo run -- regression",
"📊 Try clustering example: cargo run -- clustering",
"🔍 Run all examples at once: cargo run -- all",
"📝 Generate sample data: cargo run -- generate [classification|regression|clustering] [csv|json|all]",
"📚 See all available commands: cargo run -- help"
]
}