Predictive Analysis Tool for Predicting Student Performance and Placement Performance using ML algorithms.S. Venkat MugeshD. ThanshR. SubaashB. MuthusenthilIJARIIE
Predictive analysis can offer intelligent parametric optimization and adaptive consensus selection, which is anticipated to mitigate security threats. This allows the proposed system design to perform efficient and adaptable operations of the blockchain network under dynamic workloads and varying environments. ...
Statistical analysis of the Shapley value for microarray games. Comput. Op. Res. 37, 1413–1418 (2010). Article MathSciNet MATH Google Scholar Tarashev, N., Tsatsaronis, K. & Borio, C. Risk attribution using the Shapley value: methodology and policy applications. Rev. Finance 20, 1189...
The confidence intervals for calculating the mathematical expectation are obtained. A prototype of an electronic indicator of the takeoff trajectory with marks of predictive characteristic coordinates has been developed. 展开 DOI: 10.17587/mau.21.366-374 年份: 2020 ...
Our new embeddings have improved the running time of many important problems from least squares regression to low rank approximations, which are workhorses of statistical analysis. For instance, our running time for least squares regression is nearly optimal unless one can avoid generic matrix ...
The objective of the current research was to compare different data-driven multivariate statistical predictive algorithms for the quantitative analysis of Fe content in iron ore measured using Laser-Induced Breakdown Spectroscopy (LIBS). The algorithms investigated were Principal Components Regression (PCR)...
In this study, a database of TBM field performance from two hard rock tunneling projects in Iran including Zagros lot 1B and 2 for a total length of 14.3 km has been used to assess applicability of various analysis methods for developing reliable predictive models. The first method used for...
Fatigue analysis Nonlinear time-series analysis Model-based analysis such as residual computation, state estimation, and parameter estimation Predictive Maintenance Toolbox supplements functionality in other toolboxes such as Signal Processing Toolbox™ with functions for extracting signal-based ...
The technique of boosting a machine learning algorithm can improve its overall performance. Data scientists must understanddata preparationas a precursor to feeding data sets to machine learning models for analysis. Learn thesix steps involved in the data preparation process....
A machine learning library is a set of functions, frameworks, modules, and routines written in a given language. Developers use the code in machine learning libraries as building blocks for creating machine learning solutions that can perform complex tasks. Instead of having to manually code every...