In this article, we classify the mood of English Sentences using different pattern recognition techniques. We investigate use of a single sentence to identify the mood. We also experiment with different dimensionality reduction techniques. We used PCA reduction technic then we use j48(Decision tree), Knn and SVM algorithms for classification. In this research, we try multiple patern recognition methods to classify mood of a text data. Our data includes 750 sample sentence which could be classified under 4 different moods: happiness, anger, fear, sadness. Our data also includes the deterministic words of these sentences moods. Selection of moods and mood determinig words are done by a person so these words are subjective. We saw that unpreprocesed data gives very bad results for all of the methods (Decision tree, Knn and SVM) so we decide to implement a reduction method for further tests. In addition to this, we use the frequency analysis with letter to see what hapenned.