My cat gym

Submitted By :Nishant Arora9911103495Batch - F 1CSE

•To develop a website for CAT Preparation by using the concepts of dynamic web designing, machine learning and data analytics, so that the user not only gets the course material, but also analysis, recommendations and advice based on his/her performance.•To compare the performance of multiple machine learning algorithms for clustering and classification.

My CAT Gym is a website that would combine the features of traditional preparation system for CAT and concepts of dynamic web designing, machine learning and data analytics to become a contemporary preparation system for CAT that not only provides the basic functionalities like course material and tests, but also does their analysis and provides the user with recommendations to improve their performance so that they can excel in the CAT exam, which is the most values exam for admission to any MBA college.

Common Admission Test for Management (CAT) is an exam which is targeted by a majority of MBA aspirants. With the advancement in technology, all the course material is available on the internet. But, there is no such website that facilitates personalized training for the subjects covered in the exam, that not only provides the course material, but also advisory for the preparation. This project also serves as a testing base for comparison of performance of various classification and clustering algorithms (both unsupervised and supervised), which has also been done as a part of the project.

•K – Means Clustering Algorithm using Euclidean Distance

•K – Means Clustering Algorithm using Manhattan Distance

•Proposed Algorithm (Range Clustering)

The primary objective of this project is to provide complete guidance to the users, i. e., CAT aspirants by using the concepts of dynamic web designing, machine learning and data analytics.

In addition to what the traditional systems offer, the project would be having dedicated mechanism for categorizing analyzing a topic as the aspirants strength or weakness. This analysis would help the aspirant plan better by focusing more on the weaker are rather than repeatedly working on the area which actually don’t need that much attention.

•When a user opens the website as a guest user, he/she has access to only information part but not the features part, which are only available to the registered/ logged in users.

•When a user registers on the website, some entries are made in the progress table in the database for monitoring the status of user’s progress in his/her preparation. When the user opens a page, for example, topic notes of topic like percentages, a variable in the progress table is set for that user indicating that the user has read the topic notes of percentages. This is done for all the users, all the topics and for the features video, notes, practice questions and practice tests.

•When a registered user gives a test, his/her score, the correct answers and the incorrect answers are stored in a table in the database. Now, depending upon which algorithm has been deployed for determining the status of topic that the user just gave a test, the topic is classified as easy, moderate or tough for the user. This helps in providing a competitive and adaptive preparation to the user.

Web Designing Tools •Wordpress• PHP• HTML

Concepts of Data Analytics and Machine Learning •Clustering and Classification

CAT is one of the most popular exams that MBA aspirants give. But, till date, there has not been any solution that focuses on each aspirant individually. The package offered by coaching institutes such as Career Launcher, TIME, MBA Guru, Alchemist, etc. and by online resources like www.hitbullseye.com are not providing dedicated monitoring of user’s progress and performance.

By using the machine learning concepts, this website would be a breakthrough out of the above mentioned traditional preparation methods as it not only provides the course material in the form of videos and nutshell notes, but also personalized recommendations that help the user to plan better.

On applying different clustering and classification algorithms on the website, it has been observed that the Dynamic Average Algorithm is computationally the least expensive (script time = 1 sec) and produces the most efficient clusters and categorizes a topic the best. In the beginning when the number of users was less, k – Means Algorithm was working fine but as the number of users, and hence, the number of computations increased, it’s performance started to decrease (from script time = 4 sec to script time = 12 sec). Agglomerative Algorithm using Manhattan Distance is the least efficient of all in providing clusters, having the longest script time (>20 sec).It did not work well with the data of my website even when the number of users was less. One reason for this could be that it requires large random samples for best performance, which could not be provided by the database of my website at this point of time.

Hence, till now, the Dynamic Average Algorithm is working most efficiently.

ALGORITHM NO. OF USERS QUESTIONS FEATURES SCRIPT TIME

K MEANS - EUCLIDEAN DISTANCE 10 7 3 ~ 8 – 15 sec

K MEANS - MANHATTAN DISTANCE 10 7 3 ~ 18 – 23 sec

PROPOSED (RANGE CLUSTERING) 10 7 3 ~ 1 sec










•More efficient clustering can be done once a quality training data set is available•A feature of Live Streaming of lectures by experts in the field can be added •Question bank for practice questions as well as practice tests can be enriched•A social forum can be created where the registered users can discuss their hardships•An online library feature can be added that will have the previous year papers of various MBA entrance exams and other reference material (like, self help books)•A feature of admissions counseling can be added

Engineering

My cat gym