https://github.com/shamil-t/sentiment-analysis-using-python-imdb-

Sentiment Analysis is to find the perspective ,view ,attitude or feeling of a speaker on a particular topic, event or interactionBasicaly its the analysis of an emotionally cahrged text. Here we try to analyzethe reviewsposted by people at Imdb. Further the reviews are processed analyzed using machine learning procedures, algorithms and other related aspets.
https://github.com/shamil-t/sentiment-analysis-using-python-imdb-

ai bagging imdb-dataset machine-learning naive-bayes-classifier python random-forest sentiment-analysis support-vector-machines

Last synced: 8 months ago
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Sentiment Analysis is to find the perspective ,view ,attitude or feeling of a speaker on a particular topic, event or interactionBasicaly its the analysis of an emotionally cahrged text. Here we try to analyzethe reviewsposted by people at Imdb. Further the reviews are processed analyzed using machine learning procedures, algorithms and other related aspets.

• Host: GitHub
• URL: https://github.com/shamil-t/sentiment-analysis-using-python-imdb-
• Owner: shamil-t
• Created: 2020-06-30T00:02:31.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-08-26T13:24:29.000Z (almost 6 years ago)
• Last Synced: 2025-03-28T09:43:40.698Z (about 1 year ago)
• Topics: ai, bagging, imdb-dataset, machine-learning, naive-bayes-classifier, python, random-forest, sentiment-analysis, support-vector-machines
• Language: Python
• Homepage:
• Size: 134 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Support: Support_Machine_Vector_Classifier/imdbReview.py

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README

          
# 🆂🅴🅽🆃🅸🅼🅴🅽🆃-🅰🅽🅰🅻🆈🆂🅸🆂-🆄🆂🅸🅽🅶-🅿🆈🆃🅷🅾🅽

The principal task of Sentiment Analysis is to find the perspective ,view ,attitude or feeling of a speaker on a particular topic, event or interactionBasicaly its the analysis of an emotionally cahrged text.

	Here we try to analyzethe reviewsposted by people at Imdb. Further the reviews are processed 

analyzed using machine learning procedures, algorithms and other related aspets.

### Algorithms Used

	

	* Support Vector Machine Classifier - `linearSvc`

	* Random Forest Classifer

	* AdaBoost Classfier

	* Naive Bayes Classifier - `MultinomialNB`

	* Bagging Classifier

### Steps in Sentiment Analysis

	1.Formation of Dataset

	2.Processing of Data

	3.Creation of Feature Vector

	4.Classification

## 🅿🆁🅴 🆁🅴🆀🆄🅴🆂🆃🅸🅴🆂

### Environment Setup

 

         -:> python 2.8 or above 3.x recommended

### Dataset

[Download DataSet from here](http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz)

 then put `aclImdb` folder to parent directory

#### File structure

 ![File structure](https://github.com/shamil-t/sentiment-analysis-using-python-IMDB-/blob/master/images/Files.png?raw=true)

### install modules

1.sklearn

```bash

pip install sklearn

```

2.pickle

```bash

pip install pickle-mixin

```

3.nltk

```bash

pip install nltk

```

in Python IDLE

``` bash

import nltk

nltk.download("stopwords")

``` 

4.numpy

```bash

pip install numpy

```

## 🅷🅾🆆🆆 🆃🅾 🆁🆄🅽

`imdbReviews.py` generates `*.pkl` files which are the training and testing datasets.

First, set the dataset directory in the `imdbReviews.py`, then run the code.

```

python imdbReviews.py

```

now you will get two new .pkl files such as `test.pkl` & `train.pkl`

which are needed for `naive.py`, `svm.py`,`rfc.py`,`bagging.py`,`adaboost.py`.

#### To do prediction, run the following command.

```bash 

python filname.py 

```

`eg:-`

```bash

python naive.py

```

## ScreenShots

#### Ada Boost Classifier

![Ada Boost Classifier](https://github.com/shamil-t/sentiment-analysis-using-python-IMDB-/blob/master/images/adaboost.png?raw=true)

#### Bagging Classifier

![Bagging Classifier](https://github.com/shamil-t/sentiment-analysis-using-python-IMDB-/blob/master/images/bagging.png?raw=true)

#### Naive Bayes - MultinomialNB()

![Bagging Classifier](https://github.com/shamil-t/sentiment-analysis-using-python-IMDB-/blob/master/images/naive.png?raw=true)

#### Random Forest Classifier

![Random Forest Classifier](https://github.com/shamil-t/sentiment-analysis-using-python-IMDB-/blob/master/images/randomforest.png?raw=true)

#### Support Vector Machine - LinearSVC()

![Support Vector Machine](https://github.com/shamil-t/sentiment-analysis-using-python-IMDB-/blob/master/images/svm.png?raw=true)