topicModels | topics Models extension for Mallet & scikit-learn | Topic Modeling library

 by   chyikwei Java Version: Current License: No License

kandi X-RAY | topicModels Summary

kandi X-RAY | topicModels Summary

topicModels is a Java library typically used in Artificial Intelligence, Topic Modeling applications. topicModels has no bugs, it has no vulnerabilities and it has low support. However topicModels build file is not available. You can download it from GitHub.

topics Models extension for Mallet & scikit-learn
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            kandi-support Support

              topicModels has a low active ecosystem.
              It has 50 star(s) with 15 fork(s). There are 11 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 2 open issues and 1 have been closed. On average issues are closed in 29 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of topicModels is current.

            kandi-Quality Quality

              topicModels has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              topicModels does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              topicModels releases are not available. You will need to build from source code and install.
              topicModels has no build file. You will be need to create the build yourself to build the component from source.
              topicModels saves you 650 person hours of effort in developing the same functionality from scratch.
              It has 1508 lines of code, 77 functions and 9 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed topicModels and discovered the below as its top functions. This is intended to give you an instant insight into topicModels implemented functionality, and help decide if they suit your requirements.
            • Print test data
            • Sample topics from the input stream
            • Sample the path
            • Sampling distribution
            • Run the cross validation
            • Randomize topics
            • Initialization method
            • Updates the statistics of the document
            • Print train data
            • Print a topic distribution
            • Returns the distribution over topic distribution
            • Print test test
            Get all kandi verified functions for this library.

            topicModels Key Features

            No Key Features are available at this moment for topicModels.

            topicModels Examples and Code Snippets

            No Code Snippets are available at this moment for topicModels.

            Community Discussions

            QUESTION

            Why does loading multiple packages in R produce warnings?
            Asked 2021-Dec-27 at 20:12
            required_packs <- c("pdftools","readxl","pdfsearch","tidyverse","data.table","stringr","tidytext","dplyr","igraph","NLP","tm", "quanteda", "ggraph", "topicmodels", "lasso2", "reshape2", "FSelector")
            new_packs <- required_packs[!(required_packs %in% installed.packages()[,"Package"])]
            if(length(new_packs)) install.packages(new_packs)
            i <- 1
            for (i in 1:length(required_packs)) {
             sapply(required_packs[i],require, character.only = T)
            }
            
            ...

            ANSWER

            Answered 2021-Dec-27 at 20:12

            I think the problem is that you used T when you meant TRUE. For example,

            Source https://stackoverflow.com/questions/70497999

            QUESTION

            Error in LDA(cdes, k = K, method = "Gibbs", control = list(verbose = 25L, : Each row of the input matrix needs to contain at least one non-zero entry
            Asked 2021-Jun-04 at 06:53

            I have a big dataset of almost 90 columns and about 200k observations. One of the column contains descriptions, so it's only text. However, i have like 100 descriptions that are NAs.

            I tried the code of Pablo Barbera from GitHub concerning Topic Models because i need it.

            OUTPUT

            ...

            ANSWER

            Answered 2021-Jun-04 at 06:53

            It looks like some of your documents are empty, in the sense that they contain no counts of any feature.

            You can remove them with:

            Source https://stackoverflow.com/questions/67825501

            QUESTION

            How to get complex model using room?
            Asked 2021-Apr-10 at 02:11

            I have a UI model called CourseUiModel that I use in my ViewModel.

            ...

            ANSWER

            Answered 2021-Apr-10 at 02:11

            I believe that you want to use @Relation to build the Arrays so

            CourseUiModel could be :-

            Source https://stackoverflow.com/questions/67028341

            QUESTION

            How to chain async calls in a complex linq query
            Asked 2021-Mar-23 at 19:50

            In a .NET application, I am trying to construct a DTO on the repo layer as following. However, I have a nasty async function deep down in the statement. How should I chain the async calls?

            ...

            ANSWER

            Answered 2021-Mar-23 at 19:50

            The problem is that the lambda given to the deepest Select (.Select(async video => ...) is going to return a Task (I assume Task but not sure from the context).

            Select doesn't understand how to use a Task and will just pass it through as is. You can convert these in bulk by using WhenAll (1) but you would have to make extra provisions on the database connection, as this will execute multiple queries in parallel. (2)

            The most simple way in this instance is probably to scrap the LINQ and use foreach, like this:

            Source https://stackoverflow.com/questions/66768984

            QUESTION

            tokens_compound() in quanteda changes the order of features
            Asked 2021-Feb-20 at 08:21

            I found tokens_compound() in quanteda changes the order of tokens across different R sessions. That is, the result varies every time after restarting a session even if a seed value is fixed, though it does not change in a single session.

            Here is the replication procedure:

            1. Find collocations, compound tokens, and save them.
            ...

            ANSWER

            Answered 2021-Feb-18 at 15:09

            An interesting investigation but this is neither an error nor anything to be concerned with. Within a quanteda tokens object, the types are not determinate in order, after a processing step such as textstat_compound(). This is because this function is parallelised in C++ and how these threads operate is not fixed by set.seed() from R. But this will not affect the important part, which is the set of types, or anything about the tokens themselves. If you want the order of the types that you extract to be the same, then you should sort them upon extraction.

            Source https://stackoverflow.com/questions/66256443

            QUESTION

            topic modelling, literature. Beginner
            Asked 2021-Jan-27 at 12:09

            I am totally beginner in programming and R. I am trying to apply the topic modelling on three literature books. I try to do it having as example Silge's and Robinson's example (Text mining with R, chapter 6), with the difference that i use no preexistent list of books but a choice of mine. I meet problems, even when i applied the given code in the example i mentioned above.

            I downloaded packages (gutenbergr, tidytext, stringr, topicmodels, dplyr, tidyr) and books, and have tried to create a separate object "books" guided by the console output. I want to run the analysis by book, but i found code examples only by chapter. So i tried this:

            ...

            ANSWER

            Answered 2021-Jan-27 at 12:09

            Make books as dataframe and then you can use the functions on it. You can try :

            Source https://stackoverflow.com/questions/65900279

            QUESTION

            Error in installing "TopicModels" package in google collab
            Asked 2021-Jan-22 at 21:31

            Since I need more computational resources, I started running my R code on google collab. I have no problem with installing most of the packages I need, but for the Topicmodels package when I run the code below:

            ...

            ANSWER

            Answered 2021-Jan-22 at 21:31

            Try running this in a code cell before the installation of the topicmodels package.

            Source https://stackoverflow.com/questions/65851441

            QUESTION

            How do you combine multiple documents into a single document with topicmodels in r?
            Asked 2020-Nov-08 at 20:07

            I am currently trying to combine multiple documents of a corpus into a single document using the topicmodels package. I initially imported my data through multiple csvs, each with multiple lines of text. When I import each csv, however, each line of the csv is treated as a document, and each csv is treated as a corpus. What I would like to do is merge each of the documents/lines for each csv into a single document, and then each of the csvs would represent one document in my corpus. I'm not sure if this possible--perhaps it would be easier to somehow read in all of the lines of the csv as a single text file when initially importing and then create the docs and corpus, but I don't know how to do that either. Below is the code that I have used to import my csvs:

            ...

            ANSWER

            Answered 2020-Nov-08 at 20:07

            Your task can be accomplished with these steps:

            Source https://stackoverflow.com/questions/64741514

            QUESTION

            How to evaluate a list of tasks
            Asked 2020-Jun-18 at 20:05

            I have 2 entities: Topic.cs, Lecture.cs, a model: TopicModel.cs and an asynchronous repo call repo.GetAllLecturesAsync(string topicId). The contents of these are intuitive.

            I need to get all lectures from a repo class asynchronously and put them into a topic model. I have the following code:

            ...

            ANSWER

            Answered 2020-Jun-18 at 20:05

            QUESTION

            How to properly encode UTF-8 txt files for R topic model
            Asked 2020-May-02 at 10:20

            Similar issues have been discussed on this forum (e.g. here and here), but I have not found the one that solves my problem, so I apologize for a seemingly similar question.

            I have a set of .txt files with UTF-8 encoding (see the screenshot). I am trying to run a topic model in R using tm package. However, despite using encoding = "UTF-8" when creating the corpus, I get obvious problems with encoding. For instance, I get < U+FB01 >scal instead of fiscal, in< U+FB02>uenc instead of influence, not all punctuation is removed and some letters are unrecognizable (e.g. quotations marks are still there in some cases like view” or plan’ or ændring or orphaned quotations marks like “ and ” or zit or years—thus with a dash which should have been removed). These terms also show up in topic distribution over terms. I had some problems with encoding before, but using "encoding = "UTF-8" to create the corpus used to solve the problem. It seem like it does not help this time.

            I am on Windows 10 x64, R version 3.6.0 (2019-04-26) , 0.7-7 version of tm package (all up to date). I would greatly appreciate any advice on how to address the problem.

            ...

            ANSWER

            Answered 2020-May-02 at 10:20

            I found a workaround that seems to work correctly on the 2 example files that you supplied. What you need to do first is NFKD (Compatibility Decomposition). This splits the "fi" orthographic ligature into f and i. Luckily the stringi package can handle this. So before doing all the special text cleaning, you need to apply the function stringi::stri_trans_nfkd. You can do this in the preprocessing step just after (or before) the tolower step.

            Do read the documentation for this function and the references.

            Source https://stackoverflow.com/questions/61463661

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

            Vulnerabilities

            No vulnerabilities reported

            Install topicModels

            You can download it from GitHub.
            You can use topicModels like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the topicModels component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

            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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