Mca project download with source code

  Movie recommendation system using Collaborative filtering techniques     PROJECT ID: PYTHON17   PROJECT NAME: Movie recommendation system using Collaborative filtering techniques   PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING   PROJECT ABSTRACT: Recommender system uses the opinions of different age group users to help individuals more efficiently to find the item of their interest from a set of choices. There is a wide range of applications for recommendation system. They have become increasingly popular in last decades and are now used in every sector of online services that we approach to. These platforms are which contains movies ,music, books, social media etc. for example facebook ,it start recommending you pages similar to those you have liked recently or if u join a new organization it will start recommending you people in the same place.[1] Two main approaches widely used for recommender systems. One is content...

  Lyrics mood prediction using Decision Tree algorithm     PROJECT ID: PYTHON16   PROJECT NAME: Lyrics mood prediction using Decision Tree algorithm   PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING   PROJECT ABSTRACT: This paper presents a case-study of the effectiveness of a trained system into classifying Greek songs according to their audio characteristics or/and their lyrics into moods. We examine how the usage of different algorithms, featureset combinations and pre-processing parameters affect the precision and recall percentages of the classification process for each mood model characteristic. Experimental results indicate that the current selection of features offers accuracy results, the superiority of lyrics content over generic audio features as well as potential caveats with current research in Greek language stemming pre-processing methods. Related Work Research in mood detection and classification in musica...

  Liver disease prediction using SVM algorithm     PROJECT ID: PYTHON15   PROJECT NAME: Liver disease prediction using SVM algorithm   PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING   PROJECT ABSTRACT: In this study, the liver disease data were collected from the UCI Machine learning repository [8]. The dataset contains 583 records with 11 features including Age, Gender, TB, DB, Alkphos, Sgpt, Sgot, TP, ALB, A/G ratio, and target label. Table 1 provides a detailed description and the type of features [9]. The dataset was split into two sets that included 416 records for group 1(liver patients) and 167 records for group 2(non-liver patients). SOFTWARE REQUIREMENTS: OS                                  : Windows Python IDE          ...