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Showing 1 to 5 of 5 for “"Iris Dataset"”.

  1. Spike-Based Classification of UCI Datasets with Multi-Layer Resume-Like Tempotron

    … with the State of the Art on the Fisher Iris dataset. Our main contribution is a software implementation of the multilayer ReSuMe algorithm using the Tempotron principle. The XOR problem is solved in only 13.73 epochs on average. However, training time on four different UCI datasets is …

    central-wash Repository record for Spike-Based Classification of UCI Datasets with Multi-Layer Resume-Like Tempotron (opens in a new tab)

  2. Harnessing the power of intersection for data disaggregation: a novel similarity measure and unsupervised data-driven classification method applied to financial contagion

    … the most popular benchmark data (i.e. Fisher’s Iris dataset). Moreover, empirical results applied to a period of 15 years of real-world time series of the most relevant economies worldwide provide statistically significant evidence that the clustering structure of international stock markets …

    cambridge Repository record for Harnessing the power of intersection for data disaggregation: a novel similarity measure and unsupervised data-driven classification method applied to financial contagion (opens in a new tab)

  3. An improved algorithm for iris classification by using support vector machine and binary random machine learning

    … learning that seek to classify all the Iris dataset respect to three species (setosa, versicolor and virginica) in order them to mimic the actual dataset by using Support Vector Machine with four different kernel function (Linear, Radial Basis, Sigmoid and Polynomial), Random Forest …

    uthm Repository record for An improved algorithm for iris classification by using support vector machine and binary random machine learning (opens in a new tab)

  4. Adaptive function modal learning neural networks

    … many linearly inseparable problems, such as the Iris dataset, and a natural language phrase recognition task. A multi-layer approach, a Multi-layer ADFUNN (MADFUNN) is introduced to solve highly complex datasets. It aims to find a suitably restricted subset of neuron activation functions which …

    london-metro Repository record for Adaptive function modal learning neural networks (opens in a new tab)

  5. K-means landscapes: exploring clustering solution spaces using energy landscape theory

    … We analyse K-means landscapes for Fisher’s Iris dataset, the glass identification dataset, and many variations in which we alter their properties. For K-means the number of clusters must be prespecified, and we consider the effect of that choice on the Iris landscapes. K-means landscapes are …

    cambridge Repository record for K-means landscapes: exploring clustering solution spaces using energy landscape theory (opens in a new tab)