World of internet has a great impact on online shopping as new buyers use experience of others about the product or service. Opinion or review comment given by someone in order to ruin the reliability of the product or service is considered as Fake review or spam.Thus it is an extremely important to verify their reliability before buying product. Natural language processing techniques are widely used for spam detection. Different NLP techniques are proposed earlier for detecting the review spam such as active learning, n-gram patterns etc. This paper presents an active learning method using different classification algorithm for detecting fake and genuine reviews. The classification algorithms suggested and implemented are rough-set, decision tree, random forest and support vector machine. This paper studies the effectiveness of algorithm used for fake review detection.