Machine Learning Tools

Configuration File: packages/machine_learning_tools.json Tool Type: Local Tools Count: 21

This page contains all tools defined in the machine_learning_tools.json configuration file.

Available Tools

get_catboost_info (Type: PackageTool)

Get information about the catboost package. High-performance gradient boosting library

get_catboost_info tool specification

Tool Information:

• Name: get_catboost_info

• Type: PackageTool

• Description: Get information about the catboost package. High-performance gradient boosting library

Parameters:

No parameters required.

Example Usage:

query = {
    "name": "get_catboost_info",
    "arguments": {
    }
}
result = tu.run(query)

get_cobrapy_info (Type: PackageTool)

Get comprehensive information about COBRApy – constraint-based metabolic modeling

get_cobrapy_info tool specification

Tool Information:

• Name: get_cobrapy_info

• Type: PackageTool

• Description: Get comprehensive information about COBRApy – constraint-based metabolic modeling

Parameters:

• info_type (string) (required) Type of information to retrieve about COBRApy

Example Usage:

query = {
    "name": "get_cobrapy_info",
    "arguments": {
        "info_type": "example_value"
    }
}
result = tu.run(query)

get_deeppurpose_info (Type: PackageTool)

Get comprehensive information about DeepPurpose – deep learning toolkit for drug discovery

get_deeppurpose_info tool specification

Tool Information:

• Name: get_deeppurpose_info

• Type: PackageTool

• Description: Get comprehensive information about DeepPurpose – deep learning toolkit for drug discovery

Parameters:

• info_type (string) (required) Type of information to retrieve about DeepPurpose

Example Usage:

query = {
    "name": "get_deeppurpose_info",
    "arguments": {
        "info_type": "example_value"
    }
}
result = tu.run(query)

get_deepxde_info (Type: PackageTool)

Get comprehensive information about DeepXDE – a library for physics-informed neural networks (PIN…

get_deepxde_info tool specification

Tool Information:

• Name: get_deepxde_info

• Type: PackageTool

• Description: Get comprehensive information about DeepXDE – a library for physics-informed neural networks (PINNs) solving PDEs and inverse problems.

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and a quick-start guide

Example Usage:

query = {
    "name": "get_deepxde_info",
    "arguments": {
    }
}
result = tu.run(query)

get_faiss_info (Type: PackageTool)

Get comprehensive information about Faiss – efficient similarity search and clustering

get_faiss_info tool specification

Tool Information:

• Name: get_faiss_info

• Type: PackageTool

• Description: Get comprehensive information about Faiss – efficient similarity search and clustering

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and quick start guide

Example Usage:

query = {
    "name": "get_faiss_info",
    "arguments": {
    }
}
result = tu.run(query)

get_harmony_pytorch_info (Type: PackageTool)

Get comprehensive information about harmony-pytorch – single-cell data integration

get_harmony_pytorch_info tool specification

Tool Information:

• Name: get_harmony_pytorch_info

• Type: PackageTool

• Description: Get comprehensive information about harmony-pytorch – single-cell data integration

Parameters:

• info_type (string) (required) Type of information to retrieve about harmony-pytorch

Example Usage:

query = {
    "name": "get_harmony_pytorch_info",
    "arguments": {
        "info_type": "example_value"
    }
}
result = tu.run(query)

get_hmmlearn_info (Type: PackageTool)

Get comprehensive information about hmmlearn – Hidden Markov Models in Python

get_hmmlearn_info tool specification

Tool Information:

• Name: get_hmmlearn_info

• Type: PackageTool

• Description: Get comprehensive information about hmmlearn – Hidden Markov Models in Python

Parameters:

• info_type (string) (required) Type of information to retrieve about hmmlearn

Example Usage:

query = {
    "name": "get_hmmlearn_info",
    "arguments": {
        "info_type": "example_value"
    }
}
result = tu.run(query)

get_hyperopt_info (Type: PackageTool)

Get comprehensive information about Hyperopt – distributed hyperparameter optimization

get_hyperopt_info tool specification

Tool Information:

• Name: get_hyperopt_info

• Type: PackageTool

• Description: Get comprehensive information about Hyperopt – distributed hyperparameter optimization

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and quick start guide

Example Usage:

query = {
    "name": "get_hyperopt_info",
    "arguments": {
    }
}
result = tu.run(query)

get_imbalanced_learn_info (Type: PackageTool)

Get information about the imbalanced-learn package. Python toolbox for imbalanced dataset learning

get_imbalanced_learn_info tool specification

Tool Information:

• Name: get_imbalanced_learn_info

• Type: PackageTool

• Description: Get information about the imbalanced-learn package. Python toolbox for imbalanced dataset learning

Parameters:

No parameters required.

Example Usage:

query = {
    "name": "get_imbalanced_learn_info",
    "arguments": {
    }
}
result = tu.run(query)

get_lightgbm_info (Type: PackageTool)

Get information about the lightgbm package. Fast gradient boosting framework

get_lightgbm_info tool specification

Tool Information:

• Name: get_lightgbm_info

• Type: PackageTool

• Description: Get information about the lightgbm package. Fast gradient boosting framework

Parameters:

No parameters required.

Example Usage:

query = {
    "name": "get_lightgbm_info",
    "arguments": {
    }
}
result = tu.run(query)

get_optuna_info (Type: PackageTool)

Get information about the optuna package. Hyperparameter optimization framework

get_optuna_info tool specification

Tool Information:

• Name: get_optuna_info

• Type: PackageTool

• Description: Get information about the optuna package. Hyperparameter optimization framework

Parameters:

No parameters required.

Example Usage:

query = {
    "name": "get_optuna_info",
    "arguments": {
    }
}
result = tu.run(query)

get_pymzml_info (Type: PackageTool)

Get comprehensive information about pymzML – mzML file parser for mass spectrometry

get_pymzml_info tool specification

Tool Information:

• Name: get_pymzml_info

• Type: PackageTool

• Description: Get comprehensive information about pymzML – mzML file parser for mass spectrometry

Parameters:

• info_type (string) (required) Type of information to retrieve about pymzML

Example Usage:

query = {
    "name": "get_pymzml_info",
    "arguments": {
        "info_type": "example_value"
    }
}
result = tu.run(query)

get_python_libsbml_info (Type: PackageTool)

Get comprehensive information about python-libsbml – SBML (Systems Biology Markup Language) support

get_python_libsbml_info tool specification

Tool Information:

• Name: get_python_libsbml_info

• Type: PackageTool

• Description: Get comprehensive information about python-libsbml – SBML (Systems Biology Markup Language) support

Parameters:

• info_type (string) (required) Type of information to retrieve about python-libsbml

Example Usage:

query = {
    "name": "get_python_libsbml_info",
    "arguments": {
        "info_type": "example_value"
    }
}
result = tu.run(query)

get_pytorch_info (Type: PackageTool)

Get comprehensive information about PyTorch – an open source machine learning framework

get_pytorch_info tool specification

Tool Information:

• Name: get_pytorch_info

• Type: PackageTool

• Description: Get comprehensive information about PyTorch – an open source machine learning framework

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and quick start guide

Example Usage:

query = {
    "name": "get_pytorch_info",
    "arguments": {
    }
}
result = tu.run(query)

get_schnetpack_info (Type: PackageTool)

Get comprehensive information about SchNetPack – a deep-learning toolbox for molecules and materi…

get_schnetpack_info tool specification

Tool Information:

• Name: get_schnetpack_info

• Type: PackageTool

• Description: Get comprehensive information about SchNetPack – a deep-learning toolbox for molecules and materials built on PyTorch.

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and a quick-start guide

Example Usage:

query = {
    "name": "get_schnetpack_info",
    "arguments": {
    }
}
result = tu.run(query)

get_scikit_learn_info (Type: PackageTool)

Get comprehensive information about scikit-learn – simple and efficient tools for predictive data…

get_scikit_learn_info tool specification

Tool Information:

• Name: get_scikit_learn_info

• Type: PackageTool

• Description: Get comprehensive information about scikit-learn – simple and efficient tools for predictive data analysis

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and quick start guide

Example Usage:

query = {
    "name": "get_scikit_learn_info",
    "arguments": {
    }
}
result = tu.run(query)

get_skopt_info (Type: PackageTool)

Get information about the skopt package. Scikit-Optimize: sequential model-based optimization

get_skopt_info tool specification

Tool Information:

• Name: get_skopt_info

• Type: PackageTool

• Description: Get information about the skopt package. Scikit-Optimize: sequential model-based optimization

Parameters:

No parameters required.

Example Usage:

query = {
    "name": "get_skopt_info",
    "arguments": {
    }
}
result = tu.run(query)

get_statsmodels_info (Type: PackageTool)

Get comprehensive information about statsmodels – statistical modeling and econometrics

get_statsmodels_info tool specification

Tool Information:

• Name: get_statsmodels_info

• Type: PackageTool

• Description: Get comprehensive information about statsmodels – statistical modeling and econometrics

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and quick start guide

Example Usage:

query = {
    "name": "get_statsmodels_info",
    "arguments": {
    }
}
result = tu.run(query)

get_torch_geometric_info (Type: PackageTool)

Get comprehensive information about PyTorch Geometric – a high-performance library for graph neur…

get_torch_geometric_info tool specification

Tool Information:

• Name: get_torch_geometric_info

• Type: PackageTool

• Description: Get comprehensive information about PyTorch Geometric – a high-performance library for graph neural networks widely used in molecular and materials science.

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and quick start guide

Example Usage:

query = {
    "name": "get_torch_geometric_info",
    "arguments": {
    }
}
result = tu.run(query)

get_umap_learn_info (Type: PackageTool)

Get comprehensive information about UMAP-learn – dimensionality reduction technique

get_umap_learn_info tool specification

Tool Information:

• Name: get_umap_learn_info

• Type: PackageTool

• Description: Get comprehensive information about UMAP-learn – dimensionality reduction technique

Parameters:

• include_examples (boolean) (optional) Whether to include usage examples and quick start guide

Example Usage:

query = {
    "name": "get_umap_learn_info",
    "arguments": {
    }
}
result = tu.run(query)

get_xgboost_info (Type: PackageTool)

Get information about the xgboost package. Optimized gradient boosting framework

get_xgboost_info tool specification

Tool Information:

• Name: get_xgboost_info

• Type: PackageTool

• Description: Get information about the xgboost package. Optimized gradient boosting framework

Parameters:

No parameters required.

Example Usage:

query = {
    "name": "get_xgboost_info",
    "arguments": {
    }
}
result = tu.run(query)

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