From a866390ae3696e8a3bbc7e14a909d20111c0641f Mon Sep 17 00:00:00 2001
From: Anne Lorenz <mail@annelorenz.com>
Date: Thu, 18 Oct 2018 22:10:11 +0200
Subject: [PATCH] updated readme

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 README.md | 69 +++++++++++++++++++++++--------------------------------
 1 file changed, 29 insertions(+), 40 deletions(-)

diff --git a/README.md b/README.md
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-# Predictor for Company Mergers
-State: October 2018 (in progress)
+# Prediction of Company Mergers  (Bachelorthesis Anne)
 
-My python classes for text mining, machine learning models, …
+This project contains python classes for text mining, machine learning models, …  
+The csv file *classification_labelled_corrected.csv* contains 1497 labeled news articles from *Reuters.com* and is used for the machine learning models.
 
-The scripts can be called separately.
+**Best F1 score results**:
 
-The complete documentation can be found in the latex document in the thesis folder.
-
-The csv file 'classification_labelled_corrected.csv' contains 1497 labeled news articles from Reuters.com and is used for the machine learning models.
-
-Note: 
-Please enter a valid webhose personal key before you call 'Requester.py'.
-Also, please change the path to your JAVAHOME environment variable in 'NER.find_companies' method.
-
-example:
-java_path = "C:\\Program Files (x86)\\Java\\jre1.8.0_181"
-os.environ['JAVAHOME'] = java_path
-
-### Best F1 score results:
-
-SVM:
-
-F1 score: 0.8944166649330559
-
-best parameters set found on development set:
+* **Support Vector Machines Classifier (SVM):**  
+F1 score: 0.8944166649330559  
+Best parameters set found on development set:
 {'SVC__C': 0.1, 'SVC__gamma': 0.01, 'SVC__kernel': 'linear', 'perc__percentile': 50}
 
-Naive Bayes:
+* **Naive Bayes Classifier**:  
+F1 score: 0.8324014738144634 (average)  
+Parameters: SelectPercentile(25), own Bag of Words implementation, 10-fold cross validation  
 
-parameters: SelectPercentile(25), own BOW implementation, 10-fold cross validation
-
-F1 score: min = 0.7586206896551724, max = 0.8846153846153846, average = 0.8324014738144634
-
-
-## Requirements
-
-pandas==0.20.1
-nltk==3.2.5
-webhoseio==0.5
-numpy==1.14.0
-graphviz==0.9
-scikit_learn==0.19.2
+The complete documentation can be found in the latex document in the *thesis* folder.
 
 ## Installation under Windows
+```bash
+$ pip install xy
+```
+### Requirements  
 
-pip install XY
+pandas==0.20.1  
+nltk==3.2.5  
+webhoseio==0.5  
+numpy==1.14.0  
+graphviz==0.9  
+scikit_learn==0.19.2
 
-## Installation under UBUNTU
+## 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. 
+---
 
-apt-get install XX
+**Author:** Anne Lorenz / Datavard AG
+
+**Project Status:** work in progress
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