40 lines
1.3 KiB
Markdown
40 lines
1.3 KiB
Markdown
# Prediction of Company Mergers (Bachelorthesis Anne)
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This project contains python classes for text mining, machine learning models, …
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The csv file *classification_labelled_corrected.csv* contains 1497 labeled news articles from *Reuters.com* and is used for the machine learning models.
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**Best F1 score results**:
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* **Support Vector Machines Classifier (SVM):**
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F1 score: 0.8944166649330559
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Best parameters set found on development set:
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{'SVC__C': 0.1, 'SVC__gamma': 0.01, 'SVC__kernel': 'linear', 'perc__percentile': 50}
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* **Naive Bayes Classifier**:
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F1 score: 0.8324014738144634 (average)
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Parameters: SelectPercentile(25), own Bag of Words implementation, 10-fold cross validation
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The complete documentation can be found in the latex document in the *thesis* folder.
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## Installation under Windows
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```bash
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$ pip install xy
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```
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### Requirements
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pandas==0.20.1
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nltk==3.2.5
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webhoseio==0.5
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numpy==1.14.0
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graphviz==0.9
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scikit_learn==0.19.2
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## Usage
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The scripts can be called separately.
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You need to enter a valid personal key for *webhose.io* before you call *Requester.py*.
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To run *NER.py* you need to change the path to the JAVAHOME environment variable in *find_companies* method.
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---
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**Author:** Anne Lorenz / Datavard AG
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**Project Status:** work in progress |