dga_classifier | Sample DGA classifier
kandi X-RAY | dga_classifier Summary
kandi X-RAY | dga_classifier Summary
dga_classifier is a Python library. dga_classifier has no bugs, it has no vulnerabilities and it has low support. However dga_classifier build file is not available. You can download it from GitHub.
Sample code for wooyun article
Sample code for wooyun article
Support
Quality
Security
License
Reuse
Support
dga_classifier has a low active ecosystem.
It has 105 star(s) with 69 fork(s). There are 13 watchers for this library.
It had no major release in the last 6 months.
There are 3 open issues and 0 have been closed. On average issues are closed in 1485 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of dga_classifier is current.
Quality
dga_classifier has 0 bugs and 16 code smells.
Security
dga_classifier has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
dga_classifier code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
dga_classifier does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
dga_classifier releases are not available. You will need to build from source code and install.
dga_classifier has no build file. You will be need to create the build yourself to build the component from source.
dga_classifier saves you 164 person hours of effort in developing the same functionality from scratch.
It has 407 lines of code, 16 functions and 8 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed dga_classifier and discovered the below as its top functions. This is intended to give you an instant insight into dga_classifier implemented functionality, and help decide if they suit your requirements.
- Compute the hmm probability for the given domain
- Generate bigrams
- Return trigrams from a list of words
- Returns the number of consecutive consonant in a word
- Return the maximum match for a domain
- Count all repeat letters
- Generator for bigrams
- Return the number of consecutive digits in a word
- Calculate the average of a list
- Return the standard deviation of an array
- Count the number of vowels in a word
- Count the number of digits
Get all kandi verified functions for this library.
dga_classifier Key Features
No Key Features are available at this moment for dga_classifier.
dga_classifier Examples and Code Snippets
No Code Snippets are available at this moment for dga_classifier.
Community Discussions
Trending Discussions on dga_classifier
QUESTION
" samples: %r" % [int(l) for l in lengths]) ValueError: Found input variables with inconsistent numbers of samples: [219870, 0, 0]
Asked 2021-Jun-12 at 20:22
I'm trying to train some ML algorithms on some data that I collected, but I received an error for input variables with inconsistent numbers of samples. I'm not really sure what variables needs to be changed or not. I've posted my code below to give you a better understanding of what I'm trying to accomplish:
...ANSWER
Answered 2021-Jun-12 at 12:14The file has to be opened in binary mode.
open(DATA_FILE, 'rb')
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install dga_classifier
You can download it from GitHub.
You can use dga_classifier 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.
You can use dga_classifier 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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