hyperimpute
orange
hyperimpute | orange | |
---|---|---|
3 | 27 | |
134 | 4,633 | |
0.0% | 1.3% | |
3.5 | 9.6 | |
about 1 year ago | 4 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
hyperimpute
- HyperImpute: A tool for prototyping and benchmarking data imputation methods
-
[P] AutoPrognosis - A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
AutoPrognosis is an AutoML library for tabular data focused on survival analysis or classification tasks. The library can select optimal prediction pipelines for a given dataset and a task type and can handle data missingness using HyperImpute.
-
[P] HyperImpute: sklearn-style library for handling missing data using novel algorithms
Github page: https://github.com/vanderschaarlab/hyperimpute
orange
-
Hierarchical Clustering
I know I've tooted its horn before, but Orange3 is a pretty neat Python-based GUI platform that makes this and a metric buttload of other statistical/ML techniques available to non-programmer types.
Just watch out for null character `x00` in the corpus. That always seems to kill it stone dead.
https://orangedatamining.com/
https://orange3.readthedocs.io/projects/orange-visual-progra...
- Orange Data Mining
-
The Graph of Wikipedia [video]
For all you folks who aren't ace programmer types, the Orange3[1] platform gives you a very miniaturized[2] ability to turn out these sorts of visualizations very rapidly. It's not the most stable thing in the world, but the node-based ML workflow designer is worth the price of admission all by itself.
[1] https://orangedatamining.com/
[2] The Wikipedia extension in Text limits each search result to 25 articles, so sucking all of Wikipedia is . . well, Orange text analytics crashes when I look at it sideways with a null character, so let's not think about what would happen.
- Ask HN: What Underrated Open Source Project Deserves More Recognition?
-
Taxonomy Management?
First is identifying the "similar" things in a corpus. Best way I know to do that, for non-programmer audiences, is the Orange Data Mining tool, which gives you a node-based text mining interface to perform statistical analysis on text. Hierarchical Clustering shows - very rapidly - how similar your "modules" are, which ones are most similar. There's many other techniques (semantic viewer, similarity hash, etc) as well - the right one will depend on how your content is laying about.
- Orange: Open-source machine learning and data visualization
-
What exactly is AutoGPT?
Both tools are ripoffs of a data mining framework named Orange 3
-
Why don't more people use Altair for python Visualizations instead of Plotly?
You should also check out Orange Data Mining, it allows to create a lot of charts, filter data from a chart to another, build ML models, predictions and a lot more. And you can do it with zero code.
-
Advice on Transitioning to Data Science/ML/AI without Coding Experience
You can start with a free GUI based tool Orange. It is a component based data science workflow tool, which you can use to handle 60-75% of the traditional data science tasks from classification, regression, to basic neural networks.
- Has anybody used Orange?
What are some alternatives?
autoprognosis - A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
glue - Linked Data Visualizations Across Multiple Files
featuretools - An open source python library for automated feature engineering
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
RDKit - The official sources for the RDKit library
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
mlcourse.ai - Open Machine Learning Course
Interactive Parallel Computing with IPython - IPython Parallel: Interactive Parallel Computing in Python
NumPy - The fundamental package for scientific computing with Python.
Dask - Parallel computing with task scheduling