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Exact(23)
Because real datasets are always a combination of numeric and nominal vales, for an algorithm that only takes nominal data, numerical attributes need to be discretized into nominal attributes before the learning algorithm.
To supplement the experimental data, numerical models were also developed and validated against the test results.
The experimental data, numerical results and the analytical predictions are all agree well with each other.
Comparisons are made between measured data, numerical results, and analytical predictions.
Once validated against experimental data, numerical simulations were conducted to add to the level of details obtained from experiments.
In order to compare the simulated results with experimental data, numerical values for the heat transfer coefficients were theoretically evaluated.
Similar(37)
Then, we use following data for numerical example.
It quantifies dissimilarity between sample data for numerical computation.
Despite these limitations, the data reveal numerical trends.
Data for numerical values are presented as median (range).
We calculated proportion and mean ± standard deviation (SD) for the categorical data and numerical data, respectively.
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