The ever-increasing fame of wireless technologies and their purposefulness of usage in the communication scenario is fascinating the interest of customers day by day. As we all know that this is the recent technology within the mobile telecommunications is the 4G architecture. Long term evolution (LTE) is said to be the nominee of the next generation in the direction of 4G in mobile broadband technology, which offers a data rate of 100 Mbps and works with IP. It is recently an emerging technology and it offers enhanced speed, capacity and coverage for present mobility networks. LTE, which is considered to be an IP based network, is said to eradicate the issues present in the communication systems such as lack of resources and distributed services to the users in their day to day life. It increases the speed and capacity with improvements in core network deployment and different radio interfaces all together. In order to provide a seamless and high speed communication, customization of channel is needed for each individual user. For channel allocation, there are several methods to predict available channel and optimal usage of channel to users. By the optimal selection of channel and customized scheduling, we can manage the data transmission to users. For this process, LTE system was used to schedule the channel. However, in LTE scheduling, the scheduler has to verify the channel information, user availability and hand off status in the network. The above mentioned criterions might create some limitation during scheduling of the channel. In order to overcome this limitation, we propose a novel feature extraction method and classification method for data mining process to retrieve the information about a network for LTE scheduling. In addition to this here in this paper we have analyzed the dataset and with the help of MATLAB.