ArtificialIntelligence

Steps for Naive Bayes using sklearn(Python): Import GaussianNB: from sklearn.naivebayes import GaussianNB  Create classifier: clf = GaussianNB() Fit the classifier: clf.fit(FeatureTrainingSet,LabelTrainingSet) Prediction for testing data clf.predict(FeatureTestingSet) Accuracy is one of the metrics to check fitting of model over available dataset.There are 3 ways to check accuracy Manually calculating number of correctly predicted data set upon all dataset. Using accuracy_score metrics: import statement should be: from sklearn_metrics import accuracy_score wherever you want to check accuracy : print accuracy_score(NumpyArrayToBePredicted, labelledArray) Advantage is that you can use other available metrics as well.   Using Classifier Score: clf.score(FeatureDataTobePredicted,labelledArray) It will calculate predictions for provided data and then calculates accuracy for that data. Advantage is that you don't need to calculate predictions separa...

         I just came across with new theory regarding artificial intelligence and its progress.It might be old one, but I just came across with it.It is the presentation given with regarding the problem, we the researcher in AI faced. Even though I am still understanding the concept and I am not fully grabbing it, But I guess it gives us some different perceptive regarding development of Artificial General Intelligence.Here I am just providing a brief overview of what I understood from this.          Human Brain works in 2 disparate modes, the first one is Understanding and the other one is Reasoning.Mostly even the best of the nowadays algorithm deals with reasoning kind of problems, like playing chess and rocket science.But if we need to develop a machine which needs to meet day to day problems, it should be dealing with understanding of the Vast and Complex  real time situation which we, as human...