Download nz.ac.waikato.cms.weka.thirdparty JAR files with all dependencies
nifiLoader from group nz.ac.waikato.cms.weka (version 1.0.1)
Package for loading a directory containing MRI data in NIfTI format. The directory to be loaded must contain as many subdirectories as there are classes of MRI data. Each subdirectory name will be used as the class label for the corresponding .nii files in that subdirectory. (This is the same strategy as the one used by WEKA's TextDirectoryLoader.) Currently, the package only reads volume information for the first time slot from each .nii file. The readDoubleVol(short ttt) method from the Nifti1Dataset class (http://niftilib.sourceforge.net/java_api_html/Nifti1Dataset.html) is used to read the data for each volume into a sparse WEKA instance (with ttt=0). For an LxMxN volume (the dimensions must be the same for each .nii file in the directory!), the order of values in the generated instance is [(z_1, y_1, x_1), ..., (z_1, y_1, x_L), (z_1, y_2, x_1), ..., (z_1, y_M, x_L), (z_2, y_1, x_1), ..., (z_N, y_M, x_L)]. If the volume is an image, then only x and y coordinates are used.
jaxb-xjc from group org.andromda.thirdparty.jaxb2_commons (version 2.1.10.1)
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basic from group org.andromda.thirdparty.jaxb2_commons (version 0.4.1.5)
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tools from group org.andromda.thirdparty.jaxb2_commons (version 0.4.1.5)
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kernelLogisticRegression from group nz.ac.waikato.cms.weka (version 1.0.0)
This package contains a classifier that can be used to train a two-class kernel logistic regression model with the kernel functions that are available in WEKA. It optimises the negative log-likelihood with a quadratic penalty. Both, BFGS and conjugate gradient descent, are available as optimisation methods, but the former is normally faster. It is possible to use multiple threads, but the speed-up is generally very marginal when used with BFGS optimisation. With conjugate gradient descent optimisation, greater speed-ups can be achieved when using multiple threads. With the default kernel, the dot product kernel, this method produces results that are close to identical to those obtained using standard logistic regression in WEKA, provided a sufficiently large value for the parameter determining the size of the quadratic penalty is used in both cases.
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tape-parent from group com.indoqa.thirdparty (version 1.2.4)
A lightning fast, transactional, file-based FIFO for Android and Java.
Group: com.indoqa.thirdparty Artifact: tape-parent
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tape from group com.indoqa.thirdparty (version 1.2.4)
leastMedSquared from group nz.ac.waikato.cms.weka (version 1.0.2)
Implements a least median squared linear regression utilizing the existing weka LinearRegression class to form predictions. Least squared regression functions are generated from random subsamples of the data. The least squared regression with the lowest meadian squared error is chosen as the final model.
The basis of the algorithm is
Peter J. Rousseeuw, Annick M. Leroy (1987). Robust regression and outlier detection.
localOutlierFactor from group nz.ac.waikato.cms.weka (version 1.0.4)
A filter that applies the LOF (Local Outlier Factor) algorithm to compute an outlier score for each instance in the data. Can use multiple cores/cpus to speed up the LOF computation for large datasets. Nearest neighbor search methods and distance functions are pluggable.
For more information, see:
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jorg Sander (2000). LOF: Identifying Density-Based Local Outliers. ACM SIGMOD Record. 29(2):93-104.
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ivy-java from group fr.irit.smac.thirdparty.ivy (version 1.2.13)
Ivy is the software bus that will creep over your network!
distributedWekaHadoopCore from group nz.ac.waikato.cms.weka (version 1.0.19)
This package provides loaders and savers for HDFS, plus Hadoop jobs and tasks that wrap the tasks provided in distributedWekaBase.
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scriptingClassifiers from group nz.ac.waikato.cms.weka (version 1.0.2)
Wrapper classifiers for Jython and Groovy code. Even though the classifier is serializable, the trained classifier cannot be stored persistently. I.e., one cannot store a model file and re-load it at a later point in time again to make predictions.
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distributedWekaBase from group nz.ac.waikato.cms.weka (version 1.0.13)
This package provides generic configuration class and distributed map/reduce style tasks for Weka
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javax.transaction from group com.jwebmp.thirdparty (version 0.68.0.1)
Eclipse Project for JTA
uadetector-core from group com.jwebmp.thirdparty (version 0.68.0.1)
The UADetector core library includes the API and implementation to read the detection information and the functions to identify User-Agents, but not the database (also known as UAS data). The UAS data can be found in the resources module.
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