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Package containing a class that rescales the attributes in a classification problem based on their discriminative power. This is useful as a pre-processing step for learning algorithms such as the k-nearest-neighbour method, to replace simple normalization. Each attribute is rescaled by multiplying it with a learned weight. All attributes excluding the class are assumed to be numeric and missing values are not permitted. To achieve the rescaling, this package also contains an implementation of non-negative logistic regression, which produces a logistic regression model with non-negative weights .

PDF for Java - Open Source Edition License ? 2012 Innovatics Inc. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: - Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. - Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and / or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

PDFjet for Java and C# - Open Source Edition License ? 2012 Innovatics Inc. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: - Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. - Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and / or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Apache Commons Crypto is a cryptographic library optimized with AES-NI (Advanced Encryption Standard New Instructions). It provides Java API for both cipher level and Java stream level. Developers can use it to implement high performance AES encryption/decryption with the minimum code and effort. Please note that Crypto doesn't implement the cryptographic algorithm such as AES directly. It wraps to OpenSSL or JCE which implement the algorithms. Features -------- 1. Cipher API for low level cryptographic operations. 2. Java stream API (CryptoInputStream/CryptoOutputStream) for high level stream encryption/decryption. 3. Both optimized with high performance AES encryption/decryption. (1400 MB/s - 1700 MB/s throughput in modern Xeon processors). 4. JNI-based implementation to achieve comparable performance to the native C/C++ version based on OpenSsl. 5. Portable across various operating systems (currently only Linux/MacOSX/Windows); Apache Commons Crypto loads the library according to your machine environment (it checks system properties, `os.name` and `os.arch`). 6. Simple usage. Add the commons-crypto-(version).jar file to your classpath. Export restrictions ------------------- This distribution includes cryptographic software. The country in which you currently reside may have restrictions on the import, possession, use, and/or re-export to another country, of encryption software. BEFORE using any encryption software, please check your country's laws, regulations and policies concerning the import, possession, or use, and re-export of encryption software, to see if this is permitted. See <http://www.wassenaar.org/> for more information. The U.S. Government Department of Commerce, Bureau of Industry and Security (BIS), has classified this software as Export Commodity Control Number (ECCN) 5D002.C.1, which includes information security software using or performing cryptographic functions with asymmetric algorithms. The form and manner of this Apache Software Foundation distribution makes it eligible for export under the License Exception ENC Technology Software Unrestricted (TSU) exception (see the BIS Export Administration Regulations, Section 740.13) for both object code and source code. The following provides more details on the included cryptographic software: * Commons Crypto use [Java Cryptography Extension](http://docs.oracle.com/javase/8/docs/technotes/guides/security/crypto/CryptoSpec.html) provided by Java * Commons Crypto link to and use [OpenSSL](https://www.openssl.org/) ciphers

This module contains a more general approach to construct AlignmentAlgorithms by relying on the theoretical concept of Algebraic Dynamic Programming (ADP) as developed by Giegerich et al. ADP defines four ingredients for an alignment algorithm: 1.) A signature that defines the permitted alignment operations. Operations are just function templates with an associated arity, meaning the number of arguments it takes from the left sequence and from the right sequence. In the TCSAlignmentToolbox we have a fixed signature with the following operations: REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0) and SKIPINSERTION(0, 1) 2.) A regular tree grammar that produces alignments, that is: sequences of operations, in a restricted fashion. 3.) An algebra that can translate such trees to a cost. In the TCSAlignmentToolbox this is a Comparator. 4.) A choice function, in case of the TCSAlignmentToolbox: the strict minimum or the soft minimum. An alignment algorithm in the TCSAlignmentToolbox sense of the word then is the combination of choice function and grammar. While we provide hardcoded versions of these combinations in the main package, the adp package allows you to create your own grammars. You can combine them with a choice function by instantiating one of the Algorithm classes provided in this package with a grammar of your choice. For example: AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator); creates an alignment algorithm that implicitly produces all possible alignments your grammar can construct with the given input, translates them to a cost using the algebra/comparator you provided and applies the soft minimum to return the score. This all gets efficient by dynamic programming. Note that there is runtime overhead when using this method in comparison with the hardcoded algorithms. But for complicated grammars this is a much easier way to go. For more information on the theory, please refer to my master's thesis: "Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"