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For studies with repeated-sampling design for plantations compared with natural forests, the datasets sampled in the last time were collected.

The third reason was the enlargement of the dataset sample to its current total of 42 individuals.

3. A) The smoothness of the distribution is ultimately dependent on the dataset sample size, classifier error, number of splits, and possibly other factors.

This parameter can vary between 1 and n − 1 neighbors, where n is the dataset sample size, and is generally used to infer local and/or global manifold topology.

The values of the parameters are expected to differ depending on the dataset, sampling method and the classification algorithm.

The dataset sampler accepts the following three parameters as input: (1) Approximate number of samples (denoted as N) (2) Number of cancer types (denoted as C) (3) Similarity range (denoted as [δmin,δmax]) between samples belonging to different cancer types.

We also used datasets from China and Nigeria's World Bank Enterprise survey 2012, 2014 conducted from April 2014 to February 2015 and November 2011 to March 2013.The datasets sample size comprised of 2676 firm in 19 states of Nigeria and samples from China taken from November 2011 through March 2013 consisted of 2700 privately owned and 148 state-owned firms.

The number of replication case-control groups to be used depends on the available dataset (sample size and number of genetic markers).

The results show that, for each of the datasets, the samples of different class can be correctly identified.

In each run, we select (with equal probability and return of samples) m instances from the dataset (bootstrap sample).

It looks for the most possible distribution pattern of SFS under the constraints of given demographic parameter set that fits the real dataset sampled from the population.

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