pyod | A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection) | Predictive Analytics library

 by   yzhao062 Python Version: 1.1.3 License: BSD-2-Clause

kandi X-RAY | pyod Summary

kandi X-RAY | pyod Summary

pyod is a Python library typically used in Financial Services, Banks, Payments, Analytics, Predictive Analytics applications. pyod has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install pyod' or download it from GitHub, PyPI.

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
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            kandi-support Support

              pyod has a medium active ecosystem.
              It has 7126 star(s) with 1267 fork(s). There are 148 watchers for this library.
              There were 3 major release(s) in the last 6 months.
              There are 158 open issues and 142 have been closed. On average issues are closed in 113 days. There are 21 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of pyod is 1.1.3

            kandi-Quality Quality

              pyod has 0 bugs and 0 code smells.

            kandi-Security Security

              pyod has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              pyod code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              pyod is licensed under the BSD-2-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              pyod releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              pyod saves you 3636 person hours of effort in developing the same functionality from scratch.
              It has 10622 lines of code, 967 functions and 124 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed pyod and discovered the below as its top functions. This is intended to give you an instant insight into pyod implemented functionality, and help decide if they suit your requirements.
            • Visualize the classifier
            • Get color codes
            • Check the shape of the input dataset
            • Compute the discriminator
            • Create a discriminator
            • Create a model
            • Generate data clusters for clustering
            • Check the parameter bounds
            • Fit the model
            • Generate negative samples from a given distribution
            • Fit the VAE model
            • Compute the decision function
            • Fit the Keras model
            • Fit the classification model
            • Fit the Estimator model
            • Compute the clustering estimator
            • Compute the histogram of the classifier
            • Estimate the classifier
            • Generate a data_categorical
            • Generate training data
            • Fit the estimator
            • Plots an outlier score
            • Compute the model
            • Fit the feature space
            • Fit the PCA model
            • Plot the inliers and outliers
            Get all kandi verified functions for this library.

            pyod Key Features

            No Key Features are available at this moment for pyod.

            pyod Examples and Code Snippets

            pyod - temp do not use
            Pythondot img1Lines of Code : 210dot img1License : Non-SPDX (BSD 2-Clause "Simplified" License)
            copy iconCopy
            # -*- coding: utf-8 -*-
            """Using Auto Encoder with Outlier Detection
            """
            # Author: Yue Zhao 
            # License: BSD 2 clause
            
            from __future__ import division
            from __future__ import print_function
            
            import torch
            import numpy as np
            from sklearn.preprocessing im  
            pyod - mat file conversion
            Pythondot img2Lines of Code : 145dot img2License : Non-SPDX (BSD 2-Clause "Simplified" License)
            copy iconCopy
            '''Utility function for unifying mat files
            
            '''
            import os
            import h5py
            import scipy as sp
            import numpy as np
            
            with h5py.File(os.path.join('../datasets', 'http.mat'), 'r') as file:
                print(list(file.keys()))
                X = list(file['X'])
                y = list(file[  
            pyod - compare all models
            Pythondot img3Lines of Code : 127dot img3License : Non-SPDX (BSD 2-Clause "Simplified" License)
            copy iconCopy
            # -*- coding: utf-8 -*-
            """Compare all detection algorithms by plotting decision boundaries and
            the number of decision boundaries.
            """
            # Author: Yue Zhao 
            # License: BSD 2 clause
            
            from __future__ import division
            from __future__ import print_function
              
            copy iconCopy
            from scipy.spatial import distance
            
            A = (0.003467119 ,0.01422762 ,0.0101960126)
            B = (0.007279433  ,0.01651597  ,0.0045558849)
            C = (0.005392258  ,0.02149997  ,0.0177409387)
            D = (0.017898802  ,0.02790659  ,0.0006487222)
            E = (0.013564214  ,0.
            Python3 - TypeError: 'numpy.float64' object is not iterable
            Pythondot img5Lines of Code : 4dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            neighbors = list(filter(lambda x: x % 2 != 0, myList))
            
            optimal_k = neighbors[MSE.index(min(MSE))]
            

            Community Discussions

            QUESTION

            How to install PyCaret in AWS Glue
            Asked 2021-Jul-08 at 17:01

            How can I properly install PyCaret in AWS Glue?

            Methods I tried:

            I am using Glue Version 2.0. I used --additional-python-modules and set to pycaret as shown in the picture.

            Then I got this error log.

            ...

            ANSWER

            Answered 2021-Jul-08 at 17:01

            I reached out to AWS support. Meghana was in charge of this case.

            Here is the reply:

            Source https://stackoverflow.com/questions/68260888

            QUESTION

            Using 3rd party libraries with Pyspark
            Asked 2021-May-16 at 22:53

            I have been working with PYOD library of python and have been using LOF, LOCI and CBLOF algorithms. Now I want to move to use Pyspark. I have done some RnD on pyspark MLlib. However, I have not found Implementation of LOF, LOCI or CBLOF in Pyspark. I want to know following:

            1. Do Pyspark has LOF, LOCI, CBLOF implementation in it?
            2. If not for question 1, How can I integrate PyOD library algorithms with pyspark. So i can do preprocessing of data using PySpark and train using algorithms implemented in PyOD.

            Please share if there is some reference. Thank You

            ...

            ANSWER

            Answered 2021-May-16 at 22:53

            Those algorithms are unfortunately not available on Spark MLlib, The only way you probably can use (not really effective though, even if it works) is via UDF https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.sql.functions.udf.html?highlight=udf#pyspark.sql.functions.udf

            Source https://stackoverflow.com/questions/67266678

            QUESTION

            How to determine number of neighbors in knn in pycaret
            Asked 2021-Jan-06 at 03:17

            My question lies specifically in knn method in Anomaly Detection module of pycaret library. Usually number of k neighbors has to be specified. Like for example in PyOD library.

            How to learn what number of neighbors knn uses in pycaret library? Or does it have a default value?

            ...

            ANSWER

            Answered 2021-Jan-06 at 03:17

            you can find the number of neighbors of the constructed knn model by printing it. By default, n_neighbors=5, radius=1.0.
            I run the knn demo code locally, with:

            Source https://stackoverflow.com/questions/65588010

            QUESTION

            pandas.apply expand column ValueError: If using all scalar values, you must pass an index
            Asked 2020-Sep-02 at 10:19

            I want to apply a function to a DataFrame that returns several columns for each column in the original dataset. The apply function returns a DataFrame with columns and indexes but it still raises the error ValueError: If using all scalar values, you must pass an index.

            I've tried to set the name of the output dataframe, to set the columns as a multiindex and set the index as a multiindex but it doesn't work.

            Example: I have this input dataframe

            ...

            ANSWER

            Answered 2020-Sep-01 at 12:37

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install pyod

            You can install using 'pip install pyod' or download it from GitHub, PyPI.
            You can use pyod like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            Install
          • PyPI

            pip install pyod

          • CLONE
          • HTTPS

            https://github.com/yzhao062/pyod.git

          • CLI

            gh repo clone yzhao062/pyod

          • sshUrl

            git@github.com:yzhao062/pyod.git

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