Αποτελέσματα Αναζήτησης
This project aims to perform sentiment analysis on the IMDB movie review dataset. It utilizes deep learning techniques, particularly LSTM and Conv1D layers, to classify movie reviews into positive and negative sentiments. The model is built using Keras and GloVe embeddings for word representations.
3 Μαρ 2024 · In this paper the Long Short-Term Memory (LSTM) classifier is used for analyzing sentiments of the IMDb movie reviews. It is based on the Recurrent Neural Network (RNN) algorithm.
Explore and run machine learning code with Kaggle Notebooks | Using data from IMDB Dataset of 50K Movie Reviews.
IMDB dataset has 50K movie reviews for natural language processing or Text analytics. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training and 25,000 for testing. So, predict the number of positive and ...
25 Μαρ 2022 · PDF | On Mar 25, 2022, Ayanabha Ghosh published Sentiment Analysis of IMDb Movie Reviews : A comparative study on Performance of Hyperparameter-tuned Classification Algorithms | Find,...
10 Απρ 2019 · The study utilized a real dataset of almost 43,000 IMDB movie reviews and evaluated the performance of each classifier using different evaluation metrics such as accuracy, precision,...
The report aims to classify the sentimental representations of Internet Movie Database (IMDb) reviews via machine learning based classification on document level. The report will first remove the stop words and normalize words in the IMDb reviews to better the performance of the classification.
