For patients who have a cancer, some examples are positive and some are negative. For patients who don't have a cancer, all examples are negative. The dataset has 102K examples. The dataset is biased, 0.6% of the points are positive, the rest are negative. The dataset was made ...
Kernel Bisecting k-means Clustering for SVM Training Sample Reduction
The main clustering process consists of selecting the first unlabelled point as the cluster centre, then assigning each data point in the sample dataset to its most similar cluster centre according to both the user-defined threshold and the value of similarity function in each iteration, and ...
Spark 1.6 Notebooks (describing the various enhancements for Spark 1.6) dogfood: Various notebooks including AdTech Sample Notebook Quick Start using Python | Scala examples: Example notebooks in various stages of completion including Iris dataset k-means vs. bisecting k-means flights: Various noteboo...
making the measurement impossible. To ensure the highest possible quality of data, further 86 left-hand and 68 right-hand scans were excluded due to participants’ fingers not lying fully flat on the scanner. Thus, the final dataset consisted of measurements of the left hand from 620 (65%) ...
Instead, we focus on a full-dimensional clustering approach based on the application. The second challenge is that the result of source apportionment is sensitive to outliers. If the selected dataset for a receptor model is somewhat incorrect, the results may be inaccurate as well. More- over,...
For example, the OSD dataset, with no more than one hundred samples is eclipsed by the TOD dataset, where tens of thousands of samples are present. That fact was taken into consideration in order to obtain an unbiased analytic result. Consequently, the maximum evaluation size was set at 1000...
method 1: representive framework: pre-processing (region growing / K-means clustering) + ENet + post-processin (DenseCRF / Graph Search) method 2: Size Constrained-CNN: size constrained loss + ENet 3. transfer learning techniquesWe build the demo of transfer learning techniques:...
examined a sample of individuals aged 65–105 from the 2011–2012 Chinese Longitudinal Healthy Longevity Survey dataset and identified four distinct health lifestyle patterns among older adults. These four categories included one characterized by consistent engagement in healthy behavior (22.4% of the ...
I think I should be able to solve this with some form of kmeans clustering that restricts each cluster from having more than one member from each sample. Any ideas? Collectively, these data form the spectrum of an idealizedphysicalsample containing a mixture of each of the rows, each with ...