السلام عليكم ورحمة الله وبركاته
انا عضوة جديدة في منتداكم الرائع الذي لطالما استفدت منه ..
عندي استفسار بسيط عن خوارزميتي resample & spreadSubSample في برنامج الويكا والتي نقوم باسنخدامها في مرحلة Preprocessing
وهذا التوضيح مقدم من قبل البرنامج نفسه لكلا الخوارزميتين مع شرح للخيارات المتاحه لكلا منها ولكني لم افهم بعد ما عملهما بالضبط وعمل الاوبشنز تبعها . وجزيتم خيرا مقدماً
: resample algorithms
SYNOPSIS
Produces a random subsample of a dataset using either sampling with replacement or without replacement.
The original dataset must fit entirely in memory. The number of instances in the generated dataset may be specified. The dataset must have a nominal class attribute. If not, use the unsupervised version. The filter can be made to maintain the class distribution in the subsample, or to bias the class distribution toward a uniform distribution. When used in batch mode (i.e. in the FilteredClassifier), subsequent batches are NOT resampled.
OPTIONS
biasToUniformClass -- Whether to use bias towards a uniform class. A value of 0 leaves the class distribution as-is, a value of 1 ensures the class distribution is uniform in the output data.
invertSelection -- Inverts the selection (only if instances are drawn WITHOUT replacement).
noReplacement -- Disables the replacement of instances.
randomSeed -- Sets the random number seed for subsampling.
.sampleSizePercent -- The subsample size as a percentage of the original set.
: spreadSubSample algorithms
SYNOPSIS
Produces a random subsample of a dataset. The original dataset must fit entirely in memory. This filter allows you to specify the maximum "spread" between the rarest and most common class. For example, you may specify that there be at most a 2:1 difference in class frequencies. When used in batch mode, subsequent batches are NOT resampled.
OPTIONS
adjustWeights -- Wether instance weights will be adjusted to maintain total weight per class.
distributionSpread -- The maximum class distribution spread. (0 = no maximum spread, 1 = uniform distribution, 10 = allow at most a 10:1 ratio between the classes).
maxCount -- The maximum count for any class value (0 = unlimited).
randomSeed -- Sets the random number seed for subsampling.
