Text Classification and Sentiment Analysis Alejandro Moreo AFIRM - - PowerPoint PPT Presentation
Text Classification and Sentiment Analysis Alejandro Moreo AFIRM 16th January 2019 Alejandro Moreo Text Classification and Sentiment Analysis Overview The Toolkit: scikit-learn The Environment: Jupyter Guided Exercise: topic classification
Alejandro Moreo
AFIRM
16th January 2019
Alejandro Moreo Text Classification and Sentiment Analysis
The Toolkit: scikit-learn The Environment: Jupyter Guided Exercise: topic classification Hands-on Activities: sentiment classification Concluding Remarks
Alejandro Moreo Text Classification and Sentiment Analysis
Alejandro Moreo Text Classification and Sentiment Analysis
Alejandro Moreo Text Classification and Sentiment Analysis
We will explore scikit-learn’s tools for text analysis and text mining that instantiate the most important methods described in the lectures. Guided exercise: text classification by topic
Loading datasets: 20 Newsgroups Data preprocessing: n-grams extraction, stop-words removal, and stemming with NLTK Corpus representation: tf-idf vectorial representation Learning a classifier: Support Vector Machines Test and Evaluation of results
Alejandro Moreo Text Classification and Sentiment Analysis
The participants will create and optimize their own sentiment classifier. Concretely, we will explore: 1 Feature Selection: χ2-based filtering 2 Weighting Functions: binary, tf, tf-idf, ... 3 Parameter Optimization: get the most of the classifier 4 Comparing Learners: Logistic regression, k-NN, Naive Bayes, ... 5 Competition!
Alejandro Moreo Text Classification and Sentiment Analysis