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A variety of data re-sampling techniques are implemented in the imbalanced-learn package [1] compatible with the scikit-learn Python library. The re-sampling techniques are implemented in four different categories: undersampling the majority class, oversampling the minority class, combining over and under sampling, and ensembling sampling.
The faster Julia source code can then be used from Python, or compiled to machine code, and based that way. Nuitka compiles Python into C. [164] It works with Python 3.4 to 3.12 (and 2.6 and 2.7), for Python's main supported platforms (and Windows 7 or even Windows XP) and for Android. It claims complete support for Python 3.10, some support ...
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).
Python Tools for Visual Studio, Free and open-source plug-in for Visual Studio. Spyder, IDE for scientific programming. Vim, with "lang#python" layer enabled. [2] Visual Studio Code, an Open Source IDE for various languages, including Python. Wing IDE, cross-platform proprietary with some free versions/licenses IDE for Python.
ELKI is an open-source Java data mining toolkit that contains several anomaly detection algorithms, as well as index acceleration for them. PyOD is an open-source Python library developed specifically for anomaly detection. [56] scikit-learn is an open-source Python library that contains some algorithms for unsupervised anomaly detection.
Federated learning (also known as collaborative learning) is a machine learning technique in a setting where multiple entities (often called clients) collaboratively train a model while keeping their data decentralized, [1] rather than centrally stored. A defining characteristic of federated learning is data heterogeneity.
Pages in category "Free software programmed in Python" The following 200 pages are in this category, out of approximately 313 total. This list may not reflect recent changes .