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Attabira (Sl. No.: 4) is a Vidhan Sabha constituency of Bargarh district, Odisha. [1] This constituency includes Attabira, Attabira block and Bheden block. [2] [3] This constituency was created in 2009 in place of Melchhamunda constituency. [4] Constituency didn't existed in between 1967 & 2004.
Data reconciliation is a technique that targets at correcting measurement errors that are due to measurement noise, i.e. random errors.From a statistical point of view the main assumption is that no systematic errors exist in the set of measurements, since they may bias the reconciliation results and reduce the robustness of the reconciliation.
Data type validation is customarily carried out on one or more simple data fields. The simplest kind of data type validation verifies that the individual characters provided through user input are consistent with the expected characters of one or more known primitive data types as defined in a programming language or data storage and retrieval ...
Bargarh district lies in the western part of Odisha bordering Chhattisgarh. It borders Mahasamund and Raigarh districts of Chhattisgarh on the northwest, Jharsuguda district to the north, Sambalpur district to the east, Subarnapur and Balangir districts to the south and Nuapada district to the west.
Odisha has 172 Urban Local Bodies. [2] It has been classified into three categories Municipal Corporations or Mahānagara Pālikā is the largest local body in the state. It is generally constituted around metropolitan city, which has a population of more than 100,000. Odisha has 5 municipal corporations
There are 30 districts in Odisha. Mayurbhanj is the largest district and Jagatsinghpur is the smallest district by area. Ganjam is the largest district and Deogarh is the smallest district by population in Odisha. Bhubaneswar, the capital city of Odisha is located in Khordha district.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Data verification helps to determine whether data was accurately translated when data is transferred from one source to another, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss .