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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]
5 data sets that center around robotic failure to execute common tasks. Integer valued features such as torque and other sensor measurements. 463 Text Classification 1999 [206] L. Seabra et al. Pittsburgh Bridges Dataset Design description is given in terms of several properties of various bridges. Various bridge features are given. 108 Text
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
Open Government Data (OGD) Platform India [1] [2] or data.gov.in is a platform for supporting Open data initiative of Government of India. This portal is a single-point access to datasets, documents, services, tools and applications published by ministries, departments and organisations of the Government of India .
Entrance to NCERT campus on Aurobindo Marg, New Delhi. The National Curriculum Framework 2005 (NCF 2005) is the fourth National Curriculum Framework published in 2005 by the National Council of Educational Research and Training (NCERT) in India. Its predecessors were published in 1975, 1988, 2000.
Indian mathematics emerged in the Indian subcontinent [1] from 1200 BCE [2] until the end of the 18th century. In the classical period of Indian mathematics (400 CE to 1200 CE), important contributions were made by scholars like Aryabhata , Brahmagupta , Bhaskara II , Varāhamihira , and Madhava .
9 exact Sample variance of x: s 2 x: 11 exact Mean of y: 7.50 to 2 decimal places Sample variance of y: s 2 y: 4.125 ±0.003 Correlation between x and y: 0.816 to 3 decimal places Linear regression line y = 3.00 + 0.500x: to 2 and 3 decimal places, respectively Coefficient of determination of the linear regression: 0.67 to 2 decimal places
The bootstrap dataset is made by randomly picking objects from the original dataset. Also, it must be the same size as the original dataset. However, the difference is that the bootstrap dataset can have duplicate objects. Here is a simple example to demonstrate how it works along with the illustration below: