mlxtend adds helper modules for Python data analysis and machine learning libraries.
PyCM
vsMicrosoft ML for Apache Spark
PyCM vs Microsoft ML for Apache Spark
How do PyCM and Microsoft ML for Apache Spark compare? Here are the facts side by side: pricing, platforms, open-source status and what each one is for.
| Directory detail | PyCM | Microsoft ML for Apache Spark |
|---|---|---|
| What it is | PyCM provides a Python library for working with multiclass confusion matrices. | SynapseML provides distributed machine learning algorithms for Spark through its Python library. |
| Website | ||
| Type | Open-source project | Open-source project |
| Topic | ||
| Pricing | Not confirmed | Not confirmed |
| Platforms | Not recorded | Not recorded |
| Open source | Yes | Yes |
| Language | English | English |
| Alternatives |
Other options to consider
Sites similar to both PyCM and Microsoft ML for Apache Spark.
Machine learning pipelines can use whylogs, an open-source library for logging data quality and model performance.
Open source
24 alternatives
Python developers can use gensim for topic modeling and related natural language processing tasks.
Open source
24 alternatives
A Clojure dataframe library that runs on Spark.
Open source
24 alternatives
jSciPy provides Java scientific computing tools for signal processing, FFT, filtering, power spectral density, and DCT.
Open source
24 alternatives
Class-imbalanced machine learning is supported by imbalanced-ensemble, a toolbox for ensemble methods and datasets.
Open source
24 alternatives