sentiment | Sentiment analysis using machine learning techniques | Machine Learning library

 by   vivekn Python Version: Current License: BSD-2-Clause

kandi X-RAY | sentiment Summary

kandi X-RAY | sentiment Summary

sentiment is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. sentiment has no vulnerabilities, it has a Permissive License and it has low support. However sentiment has 1 bugs and it build file is not available. You can download it from GitHub.

Sentiment analysis using machine learning techniques. Check info.py for the training and testing code. A demo of the tool is available [here] Refer this paper for more information about the algorithms used.
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              sentiment has a low active ecosystem.
              It has 422 star(s) with 183 fork(s). There are 37 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 7 open issues and 8 have been closed. On average issues are closed in 107 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of sentiment is current.

            kandi-Quality Quality

              sentiment has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 24 code smells.

            kandi-Security Security

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

            kandi-License License

              sentiment 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

              sentiment releases are not available. You will need to build from source code and install.
              sentiment has no build file. You will be need to create the build yourself to build the component from source.
              sentiment saves you 124 person hours of effort in developing the same functionality from scratch.
              It has 312 lines of code, 27 functions and 4 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed sentiment and discovered the below as its top functions. This is intended to give you an instant insight into sentiment implemented functionality, and help decide if they suit your requirements.
            • Write a file
            • Transform a text file
            Get all kandi verified functions for this library.

            sentiment Key Features

            No Key Features are available at this moment for sentiment.

            sentiment Examples and Code Snippets

            No Code Snippets are available at this moment for sentiment.

            Community Discussions

            QUESTION

            How do I show the other sentiment scores from text classification?
            Asked 2021-Jun-15 at 17:15

            I am doing sentiment analysis, and I was wondering how to show the other sentiment scores from classifying my sentence: "Tesla's stock just increased by 20%."

            I have three sentiments: positive, negative and neutral.

            This is my code, which contains the sentence I want to classify:

            ...

            ANSWER

            Answered 2021-Jun-15 at 14:44

            Because HappyTransformer does not support multi class probabilities I suggest to use another library. The library flair provides even more functionality and can give you your desired multi class probabilities, with something like this:

            Source https://stackoverflow.com/questions/67987738

            QUESTION

            Paysify sentiment api returning null
            Asked 2021-Jun-13 at 13:53

            Good day fam. I have this sentiment analysis API from Paysify, which returns a JSON output but all of a sudden it is now returning NULL as output. Please I help here, I have been trying to fix this for the past 4 hours, no headway.

            ...

            ANSWER

            Answered 2021-Jun-13 at 13:53

            This issue is not related to your code. The service you use has an issue on their server. If you try to open your Chrome browser and navigate to https://api.paysify.com/sentiment?api_key={key}&string=I+love+this+product you will see that the page can not be opened for an SSL error.

            Please contact your API provider to resolve.

            PS: remove the API Key from your initial question or anyone can use it.

            Source https://stackoverflow.com/questions/67958953

            QUESTION

            Force BERT transformer to use CUDA
            Asked 2021-Jun-13 at 09:57

            I want to force the Huggingface transformer (BERT) to make use of CUDA. nvidia-smi showed that all my CPU cores were maxed out during the code execution, but my GPU was at 0% utilization. Unfortunately, I'm new to the Hugginface library as well as PyTorch and don't know where to place the CUDA attributes device = cuda:0 or .to(cuda:0).

            The code below is basically a customized part from german sentiment BERT working example

            ...

            ANSWER

            Answered 2021-Jun-12 at 16:19

            You can make the entire class inherit torch.nn.Module like so:

            Source https://stackoverflow.com/questions/67948945

            QUESTION

            ValueError: Number of Coefficients does not match number of features (Mglearn visualization)
            Asked 2021-Jun-09 at 19:25

            I am trying to perform a sentiment analysis based on product reviews collected from various websites. I've been able to follow along with the below article until it gets to the model coefficient visualization step.

            https://towardsdatascience.com/how-a-simple-algorithm-classifies-texts-with-moderate-accuracy-79f0cd9eb47

            When I run my program, I get the following error:

            ...

            ANSWER

            Answered 2021-Jun-09 at 19:25

            You've defined feature_names in terms of the features from a CountVectorizer with the default stop_words=None, but your model in the last bit of code is using a TfidfVectorizer with stop_words='english'. Use instead

            Source https://stackoverflow.com/questions/67907780

            QUESTION

            Why are all my classification accuracy scores the same?
            Asked 2021-Jun-08 at 00:47

            I'm running several machine learning models to find the one which the highest accuracy score, however, all the accuracy scores are the exact same. I performed NLP on social media text and I'm training my models to tag sentiment based on sentiment determined from NLTK.

            I'm using the same training and test sets, but I've done this method before in the past and received different scores on different models. Why are all of mine the same? Am I overfitting perhaps?

            Here is my code where I'm splitting and training:

            ...

            ANSWER

            Answered 2021-Jun-08 at 00:47

            I'm not sure what is the cause of the problem, but since the output of you SVM model and DecisionTreeClassfier always output 1, I suggest you try a more complex model like RandomForestClassifier and see what it comes out.

            I've similar experience before, no matter how I tuned the training hyperparameters, the model always give the same performance metric -- this may cause by 2 probabilities:

            1. Our data is not suitable for the model, for example all values in the vector is zero: [0, 0, 0, 0, 0, 0, 0]
            2. Our model is too simple, which could only perform linear modeling, so that it could not learn too complex mapping function.

            Since your SVM is built with linear kernel, could you try an more complex model and see what it comes out? And could you examine that if your X_train_vectors is all zero's in the matrix?

            Source https://stackoverflow.com/questions/67878862

            QUESTION

            I can't display both widget in Python
            Asked 2021-Jun-07 at 16:52

            I'm just starting to learn python and I'm having problem with displaying two widget at the same time. I was trying to create a Text area where I will put a string then submit this string. This string will be use in SentimentIntensityAnalyzer to check the sentiment.

            My goal now is to display the two widget using ipywidgets below is my code

            ...

            ANSWER

            Answered 2021-Jun-07 at 16:52

            I used IPython.display again, my wrong way is that I put the both variables inside the display()

            Here's my code

            Source https://stackoverflow.com/questions/67872918

            QUESTION

            Setting up a gcloud appspot domain for a flask api- Getting URL not found error
            Asked 2021-Jun-07 at 00:51

            I am currently trying to setup a gcloud appspot domain. I am consistently getting this error when I attempt to open up my appspot project on the browser:

            Error: Not Found The requested URL / was not found on this server.

            Here is my code. How can I fix this?

            app.yaml -

            ...

            ANSWER

            Answered 2021-Jun-07 at 00:51

            What you're trying to deploy on App Engine is a web app. You cannot deploy Android apps on App Engine. If you look at the picture in the Final System section, the system has two main parts and that is your Android app (client) and a request server. You are deploying the request server in App Engine Flex (which is a managed Compute Engine VM under the hood).

            From what I can understand, your request server is designed to handle backend API calls. If you want to display some sort of UI interface when users access /, then register the URL to a function that renders your view page.

            I suggest that you study how Flask app routing works. You get that error because the URL (/) is not associated to any of your functions on your app. You can get started at Flask docs. Here's a sample from GitHub

            Source https://stackoverflow.com/questions/67813524

            QUESTION

            (ValueError: Columns must be same length as key) from sentiment analysis
            Asked 2021-Jun-06 at 20:52

            I have been executing a sentiment analysis, and have returned the positive and negative outcomes to my pd.DataFrame in the following manner.

            author Text Sentiment 12323 this is text (0.25, 0.35)

            However, when I want to split the sentiment column (which consists of Polarity and Subjectivity), I get the following error:

            ValueError: Columns must be same length as key

            I have tried multiple approaches:

            • str.split
            • str.extract
            • rounding

            With the rounding approach I get an error mentioning the float NaN's could not be multiplied. So I suppose that there is a NaN in there somewhere. However, when I look for NaN's I get this answer:

            ...

            ANSWER

            Answered 2021-Jun-06 at 20:52

            Edit: changed case from df['sentiment'] to df['Sentiment']

            The string methods won't work because it's not a string but a set stored in the cell.

            You can do this to create a new column:

            Source https://stackoverflow.com/questions/67833669

            QUESTION

            Streamlining cleaning Tweet text with Stringr
            Asked 2021-Jun-05 at 11:17

            I am learning about text mining and rTweet and I am currently brainstorming on the easiest way to clean text obtained from tweets. I have been using the method recommended on this link to remove URLs, remove anything other than English letters or space, remove stopwords, remove extra whitespace, remove numbers, remove punctuations.

            This method uses both gsub and tm_map() and I was wondering if it was possible to stream line the cleaning process using stringr to simply add them to a cleaning pipe line. I saw an answer in the site that recommended the following function but for some reason I am unable to run it.

            ...

            ANSWER

            Answered 2021-Jun-05 at 02:52

            To answer your primary question, the clean_tweets() function is not working in the line "Clean <- tweets %>% clean_tweets" presumably because you are feeding it a dataframe. However, the function's internals (i.e., the str_ functions) require character vectors (strings).

            cleaning issue

            I say "presumably" here because I'm not sure what your tweets object looks like, so I can't be sure. However, at least on your test data, the following solves the problem.

            Source https://stackoverflow.com/questions/67845605

            QUESTION

            When plotting two datasets and one of them has much more data, how do we "normalize" them so they're equal in representation?
            Asked 2021-Jun-03 at 12:18

            I'm using Plotly to plot some sentiment data yet I have the issue that one character has much more lines than the other so it seems that we cannot compare the two. I'm unsure how to describe for this to find the solution so I hoped that perhaps someone will understand what I'm referring to. Here are images:

            We cannot really compare orange's negativity with blue's negativity, or can we? Should we have the orange have 600 as the label, it being much smaller than blue or is this correctly scaled?

            I'd like this so we can say that for example, blue is less positive than orange.

            I'm sorry for any confusion. Thank you.

            ...

            ANSWER

            Answered 2021-Jun-03 at 12:18

            I don't know which objects you are manipulating, but I read pandas in your tags so I assumed it was a DataFrame.

            Source https://stackoverflow.com/questions/67820928

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

            Vulnerabilities

            No vulnerabilities reported

            Install sentiment

            You can download it from GitHub.
            You can use sentiment 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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