Software Downloads for "Lotto Pattern Analysis"

Screen, Scan & Filter Stocks, covers over 30 stock exchange worldwide. Provides Technical Analysis filters & Pattern Analysis filters (Japanese Candlestick). Build-in 46 filters. MACD, MACD Histogram, MACD Fast Line, MACD Slow Line, MACD Buy Signal, RSI, Moving Average (MA), MA crossover, CCI, Williams %R, MFI, Volume, Price, Evening, Morning, Shooting Star, Dragonfly & Gravestone Doji, Bullish & Bearish Engulfing, Harami, Piercing Line, Hammer, Rising Three Method, Falling Three Method, Three Black Crows and more.

  • Platform: Windows
  • Publisher: Zeebob Software
  • Date: 01-01-2005
  • Size: 8768 KB
  • baduK
  • License: Freeware
  • Rating

baduK is a pattern analysis and search engine for the game of Go/Baduk/Weiqi. An ancient boardgame common in Japan, Korea, China and Taiwan. Features multiple databases, game previews and instant pattern matches. Developed using C++ and Qt 4.1.4.

Gradient pattern analysis (GPA)[] is a geometric computing method for characterizing symmetry breaking of an ensemble of asymmetric vectors regularly distributed in a square lattice..

Jensor is a light-weight, low-overhead Java Profiler built using Java BCI. Jensor provides innovative analysis modules like JVM Replay, Pattern Analysis and Tagging Engine for technical as well as business analysis based on the same underlying data..

KNeTS (Knowledge Elicitation Tools) is a survey tool to create multi-agent models based on local knowledge using pattern analysis to identify rules that are iteratively validated with the informant. The final output is a knowledge-based multi-agent model.

Two source code files of the mRMR (minimum-redundancy maximum-relevancy) feature selection method in (Peng et al, 2005 and Ding & Peng, 2005, 2003), whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent publications. This version uses mutual information as a proxy for computing relevance and redundancy among variables (features). Other variations such as using correlation or F-test or distances can be easily implemented within this framework, too.

  • Platform: Matlab, Scripts
  • Publisher: Hanchuan Peng
  • Date: 02-06-2013
  • Size: 10 KB

Performs neural spike pattern analysis on extracellular potentials acquired with TDT's System3 and OpenEx software. More on current functions: All-Order Inter-Spike Interval Histogram. Inter-Spike Interval Histogram for any order or combination of orders. First-Order Inter-Spike Interval Histogram. Period Histogram, Synchronicity or 'Vector Strength', and Rayleigh Statistic Raster Plot, Peri-Stimulus-Time Histogram, Average Onset Latency, and Spike Counts Check back often for bugfixes and improvements.

  • Platform: Matlab, Scripts
  • Publisher: Hazem Baqaen
  • Date: 25-02-2013
  • Size: 61 KB

In the attached .zip folder you the main, self-contained function titled RelaxLabel2D which performs nonlinear relaxation labelling of 2D monochromatic and multispectral images. Also included are three demo files: RelaxLabel2D_demo1: Provides an example on how to regularize binary images corrupted by spurious noise artifacts. RelaxLabel2D_demo2: Shows how to segment color images using k-means clustering and then regularize the result by probabilistic relaxation. This demo uses my own implementation of bisecting k-means, which can provide robust and consistent initialization of cluster centroids.

  • Platform: Matlab, Scripts
  • Publisher: Anton Semechko
  • Date: 22-03-2013
  • Size: 819 KB

MyMind2UrMind is a computer language translator which uses pattern analysis rules and machine learning methods to progressively migrate code from one language to another.
MyMind2UrMind License - GNU General Public License (GPL).

A tool for detecting design patterns in Java bytecode
Structural Pattern Analysis for Java License - GNU Library or Lesser General Public License (LGPL).

  • Platform: WinOther
  • Publisher: Spa4j
  • Date:

MB Astrology Planetary Patterns Software finds the planetary patterns as they are displayed in your astrology natal chart and tells you the influences of the astrological planets considering their planetary patterns or planet positions. The interpretation of planetary patterns as delivered by MB Astrology Planetary Patterns Software includes the influences of the planets as they vary according to the locomotive pattern, splash pattern and bundle pattern. The influences of the astrology planets on the various aspects of the personal as well as professional lives of the individuals depend very much on the planet patterns at the time of your birth.

The New lottery software - Windows Lotto007 For Lotto lottery software is a professional lottery analysis software, than anything else out there because...
Easy to learn! You don't need to be a 'techie' to figure it out.
Easy to work with Smart number wizard picks the lottery numbers to play based on an analysis of the previous drawings.
Works with all Lotto lottery games! Pick-4, Pick 5, Pick-6 and Pick-7.
Supper lotto wheeling systems, works with all Pick 3, Pick 4, Pick 5, Pick 6, Pick 7 wheels.

CastleLotto makes it easy for you to analyze winning Lotto numbers, and helps you to enhance your chances of winning Lotto in the future. CastleLotto helps you maintain a database of past Lotto results, which it uses to analyze the most commonly drawn numbers, and forecasts the numbers which are most likely to appear in the next draw. As well as the powerful analysis options in CastleLotto, you also have the ability to generate weighted random numbers, which combine random chance and the benefit of trends in past results.

The Refined Elliott Trader pattern recognition software from is the World's #1 in Elliott Wave Analysis, market forecasting, and price/time projections. Elliott Wave Patterns have been used by traders to successful forecast market direction since they were first discovered in 1930. More specifically, Eliott Wave gives you price time targets for the completion of specific patterns. In 2001 Elliottician began a 5 year 10 million Elliot Wave pattern statistical study which validated and verified the existence of REAL MARKET PATTERNS.

This package is the mRMR (minimum-redundancy maximum-relevancy) feature selection method in (Peng et al, 2005 and Ding & Peng, 2005, 2003), whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent publications. This version uses mutual information as a proxy for computing relevance and redundancy among variables (features). Other variations such as using correlation or F-test or distances can be easily implemented within this framework, too.

  • Platform: Matlab, Scripts
  • Publisher: Hanchuan Peng
  • Date: 19-03-2013
  • Size: 532 KB

tensorRelightingDemo.m demonstrates the use of the Cartesian Tensor basis for facial Apparent BRDF (ABRDF) estimation and subsequent relighting. Given a few images of a face under different point source illuminations, the included code for ABRDF estimation can interpolate and extrapolate them to generate new images. Please cite the following paper if you find this code useful: Ritwik Kumar, Angelos Barmpoutis, Arunava Banerjee, Baba C. Vemuri, 'Non-Lambertian Reflectance Modeling and Shape Recovery of Faces using Tensor Splines', IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2009.

  • Platform: Matlab, Scripts
  • Publisher: Ritwik Kumar
  • Date: 17-04-2013
  • Size: 1526 KB

There are four ensemble strategies--- random selecting samples, Bagging strategy, Random subspace method, Rotation forest method. They are ensemble methods which can obtain the samples of individual learner. Bagging method is a classical ensemble strategy proposed by Leo Breiman in Ref [L.Breiman. Bagging Predictors. Machine learning, vol.24(2), pp.123-140, 1996.]. Random subspace method is proposed by Tin Kam Ho in Ref [Ho T.K.. The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on pattern analysis and Machine Intelligence, vol.

  • Platform: Matlab, Scripts
  • Publisher: Lisa
  • Date: 27-02-2013
  • Size: 10 KB

The DEMO includes 5 feature selection algorithms: * Sequential Forward Selection (SFS) * Sequential Floating Forward Selection (SFFS) * Sequential Backward Selection (SBS) * Sequential Floating Backward Selection (SFBS) * ReliefF Two CCR estimation methods: * Cross-validation * Resubstitution After selecting the best feature subset, the classifier obtained can be used for classifying any pattern. Figure: Upper panel is the pattern x feature matrix Lower panel left are the features selected Lower panel right is the CCR curve during feature selection steps Right panel is the classification results of some patterns.

The Mahalanobis distance between a pattern measurement vector of dimensionality D and the center of the class it belongs to is distributed as a chi^2 with D degrees of freedom, when an infinite training set is used. However, the distribution of Mahalanobis distance becomes either Fisher or Beta depending on whether cross-validation or re-substitution is used for parameter estimation in finite training sets. The total variation between chi^2 and Fisher as well as between chi^2 and Beta allows us to measure the information loss in high dimensions.

Synteniser is an application for visual synteny analysis using an adaptation of the Smith-Waterman sequence alignment algorithm to work at the gene rather than the nucleotide level. Synteniser also includes BRH and pattern analysis algorithms.
Synteniser: the visual synteny analyser License - Affero GNU Public License.

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