updated Readme

README.md

@@ -1,22 +1,10 @@
-# Anne's Bachelor Thesis
+# Predictor for Company Mergers
 State: October 2018 (in progress)
 
 My python classes for text mining, machine learning models, …
+
 The scripts can be called separately.
 
-Best F1 score results were:
-
-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
------------
-parameters: SelectPercentile(25), own BOW implementation, 10-fold cross validation
-F1 score: min = 0.7586206896551724, max = 0.8846153846153846, average = 0.8324014738144634
-
 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.
@@ -26,10 +14,24 @@ 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:
-# set paths
 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:
+{'SVC__C': 0.1, 'SVC__gamma': 0.01, 'SVC__kernel': 'linear', 'perc__percentile': 50}
+
+Naive Bayes:
+
+parameters: SelectPercentile(25), own BOW implementation, 10-fold cross validation
+
+F1 score: min = 0.7586206896551724, max = 0.8846153846153846, average = 0.8324014738144634
+
 
 ## Requirements