The on-demand availability of computer system resources such as data storage and computing power is cloud
computing. Scheduling is the method of allocating jobs onto resources in time. Scheduling increases the efficiency and
performance of cloud environment by maximizing the resource utilization. This scheduling process has to respect constraints
given by the jobs and the cloud providers. Ordering the tasks by scheduler along with maintaining the balance between Quality
of Service (QoS), fairness and efficiency of jobs is difficult. Scheduling algorithms are designed and implemented considering
some parameters like latency, cost, priority, etc. This paper proposes a method for task scheduling in cloud using a three-stage
method. The first stage makes use of historical scheduling data to classify tasks. Based on this VMs are created. In the second
stage newly arrived tasks are considered. Based on Bayes classifier principle a matching degree is calculated to mark a task with
a VM Type.
