# Predictor for Company Mergers    
(Bachelorthesis Anne)

This project contains python classes for text mining and machine learning models to recognize company mergers in news articles.
The csv file *classification_labelled_corrected.csv* contains 1497 labeled news articles from *Reuters.com* and is used for the machine learning models.

**Best F1 score results**:

* **Support Vector Machines Classifier (SVM):**  
F1 score: 0.894  
Best parameters set found on development set:
{'SVC\__C': 0.1, 'SVC\__gamma': 0.01, 'SVC\__kernel': 'linear', 'perc\__percentile': 50}

* **Naive Bayes Classifier**:  
F1 score: 0.841 (average)  
Parameters: SelectPercentile(100), own Bag of Words implementation, 10-fold cross validation  

The complete documentation can be found in the latex document in the *thesis* folder.

## Installation under Windows
```bash
$ pip install xy
```
### Requirements  

pandas==0.20.1  
nltk==3.2.5  
webhoseio==0.5  
numpy==1.14.0  
graphviz==0.9  
scikit_learn==0.19.2

## Usage  
The scripts can be called separately.
You need to enter a valid personal key for *webhose.io* before you call *Requester.py*.
To run *NER.py* you need to change the path to the *JAVAHOME* environment variable in *find_companies* method. 

---
**Author:** Anne Lorenz / Datavard AG

**Project Status:** work in progress