Cheapjack | download manager providing an interface | iOS library

 by   Gurpartap Swift Version: Current License: MIT

kandi X-RAY | Cheapjack Summary

kandi X-RAY | Cheapjack Summary

Cheapjack is a Swift library typically used in Mobile, iOS, Xcode applications. Cheapjack has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

A drop-in framework for adding a background download manager to your iOS app. CheapjackExample project, as pictured above, demonstrates downloading multiple files and displaying their states in a custom UITableViewCell. For advanced usage and control over downloads refer to definitions in Cheapjack.swift. Cheapjack's pretty simple to use.
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              Cheapjack has a low active ecosystem.
              It has 49 star(s) with 10 fork(s). There are 8 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 4 open issues and 0 have been closed. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of Cheapjack is current.

            kandi-Quality Quality

              Cheapjack has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              Cheapjack is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              Cheapjack releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.

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            Cheapjack Key Features

            No Key Features are available at this moment for Cheapjack.

            Cheapjack Examples and Code Snippets

            No Code Snippets are available at this moment for Cheapjack.

            Community Discussions

            QUESTION

            Why is my bagOfWord naive bayes algorithm performing worse than wekas StringToWordVector?
            Asked 2017-Dec-28 at 07:18

            I'm trying to build a naive bayes based classifier for 1000 positive+negative labled IMDB reviews (txt_sentoken) and weka API for Java.

            As I wasn't aware of StringToWordVector, which basically provides a BagOfWords model that reaches an 80% accuracy, so I did the vocabulary building and vector creation myself, with an accuracy of only 75% :(

            Now I'm wondering why my solution is performing so much worse.

            1) From my 2000 reviews, I build the BagOfWords:

            ...

            ANSWER

            Answered 2017-Dec-28 at 07:18

            Reading through Weka's StringToWordVector documentation, there seem to be a couple of implementation details different than yours. Here are the top two, based on how likely they are to be the reason for the performance difference you see, in my opinion:

            • It seems that by default, the resulting vector is boolean (i.e. noting the existence of a word, rather than number of occurrences)
            • If the class attribute is set before vectorizing the text, a separate dictionary is built for each class, then all dictionaries are merged.

            While any of them (or other, more minor differences) could be the culprit, my bet is on the second point.

            The built-in class allows setting and unsetting each of these options; you could try re-running the 80% version using StringToWordVector with the -C option to use number of occurences rather then a boolean value, and with -O, to use a single dictionary across both classes.

            This should allow you to verify whether any of these is indeed the culprit.

            EDIT: Regarding the first point, i.e. counting occurences vs. noting word existence (also called Bernoulli and multinomial models), there were several academic papers at the 90s which looked into the differences, e.g. here and here. While usually the multinomial model works better, there are also opposite cases, depending on corpus and classification problem.

            Source https://stackoverflow.com/questions/47951551

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

            Vulnerabilities

            No vulnerabilities reported

            Install Cheapjack

            You can download it from GitHub.

            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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          • HTTPS

            https://github.com/Gurpartap/Cheapjack.git

          • CLI

            gh repo clone Gurpartap/Cheapjack

          • sshUrl

            git@github.com:Gurpartap/Cheapjack.git

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