Data selection

Training is a computer controlled process that once started, it might be stopped when either of the next conditions is fulfilled maximum number of training epochs has elapsed, training and testing errors have reached an acceptable level or there is no more improvement in learning with further iterations. 

The third set, the external set is used to check performance of the trained network, and to compare with other configuration or topologies. At the end of training process a well-fit model is the desired result. If the network has properly trained then it will be able to generalize to unknown input data with the same relationship it has learned. This capability is evaluated with the test data set by feeding in these values and computing the output error. 

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Judgment had to be exercised in data selection. For each fluid, all available data were first fit simultaneously and second, in groups of authors. Data that were obviously very old, data that were obviously in error, and data that were inconsistent with the rest of the data, were removed. 

Data Mining is the core of the more comprehensive process of knowledge dis-coveiy in data bases (KDD). However, the term data mining" is often used synonymously with KDD. KDD describes the process of extracting and storing data and also includes methods for data preparation such as data cleaning, data selection, and data transformation as well as evaluation, presentation, and visualization of the results after the data mining process. 

Data integrity checking, data selection, data normalization and storage... 

Finally, it is necessary to select values for the thermodynamic constants that are to be used in equation (9). The data selected were that published by Beesley and Scott [2], for the two enantiomers, (S) and (R) 4-benzyl-2-oxazolidinone. The values for the standard free enthalpy and standard free entropy for the (R) isomer were... 

This chapter contains tables of generic equipment failure rate data for some of the CPI equipment types listed in Appendix A, the CCPS Taxonomy, or in Appendix B, the Equipment Index. Section 5.1 on data selection explains how data were selected from resources and lists which resources in Chapter 4 were used to provide data. 

Failure rate data selected for the CCPS Generic Failure Rate Data Base were handled using dBase III Data Management in conjunction with the Computerized Aggregation of Reliability Parameters (CARP) developed by SAIC. CARP, designed to be used by... 

Data selected from Changing to the Metric System, Metals and Materials, Inst, of Metallurgists, 370, Dec. <1968). 

Source Data selected from Smith, J. M., Van Ness, H. C., and Abbott, M. M., Introduction to Chemical Engineering Thermodynamics, 6th ed., McGraw-Hill, New York, 2001. 

TABLE 2—Friction coefficient of CNx films—Data selected from published articles. 

Across the top there is a menu bar with the usual Windows-type pull-down menus arranged from left to right in the order Files, Data Selection, Data Manipulation, Extras/Options, Output, or similar. Those options that are allowed or make sense in a given context are activated. Requests for numerical input make use of the standard Windows-type gray box with the question that is to be answered, the white area into which the data is written, and the appropriate confirmatory Yes/No/Cancel buttons. 

W. Wu and D.L. Massart, Artificial neural networks in classification of Nir spectral data selection of the input. Chemom. Intell. Lab. Syst., 35 (1996) 127-135. 

Step 1. Separate the initial data into two sets, corresponding to temperatures above and below Tb. Step 2. Make an initial selection from the low temperature set by rejecting all points with zero uncertainty and all points with uncertainties above a limit determined by the data selection algorithm described in section 1.5.2. Zero uncertainties are assigned to values that are not experimental and are included for comparison only (these are most often values recommended in other compilations). 

Step 3. Determine the effective number of data values, ne, as described in 1.5.3. If the effective number of values is less than four, terminate the calculation. If the total number of values is more than eight and the effective number is greater than or equal to four but less than eight, make another initial data selection with relaxed selection criteria. 

Step 10. Apply the initial data selection described in step 2 to the high temperature data set. 

McLeod gauge ebulliometry summary of literature data selected values ... 

Ebulliometry Summary of literature data Selected values From solute fugacity f and x... 

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