Download BayesiaLab v3.3 keygen by DIGERATI
| Added to site | 2005-06-05 |
| Rating | 85/100 |
| Votes | 4 |
BayesiaLab.v3.3.keygen.zip (208665 bytes)
| name | size | compressed |
|---|---|---|
| BayesiaLab.v3.3.keygen.exe | 220672 | 204316 |
| DIGERATI.nfo | 17242 | 3855 |
| FILE_ID.DIZ | 44 | 44 |
DIGERATI.nfo
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▀███▓███▓▀▀ The diGERATi Present ▀▀▓███▓███▀
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█▄▄▄▄▄ BayesiaLab v3.3 ▄▄▄▄▄▄█
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███▀ Release Info ▀██▓
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▐█▓▓ Cracker ......: DIGERATI Release-Type..: Regged ██▓▌
██▓▌ Packager......: DIGPACKER Release-Date..: 5-6-2005 ▐██▓
██▓ Supplier......: DIGERATI Protection....: Serial ██▓
▐██ Coder.........: DIGERATI OS............: WinAll █▓▌
██▓ ░ Company.......: Bayesia Disks.........: [xx/03] ░▓█▓
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▀██░ URL: http://www.bayesia.com/ ░█▓▀
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█▓█ With BayesiaLab, Bayesia gives you a complete ██▓
█▓█ laboratory for manipulating Bayesian networks: ██▓
█▓█ ██▓
█▓█ * Develop your decision models through ██▓
█▓█ expertise ██▓
█▓█ o Ergonomic node edition ██▓
█▓█ panel providing: ██▓
█▓█ + wizards for ██▓
█▓█ modality generation and naming of both Label ██▓
█▓█ and Interval nodes ██▓
█▓█ + various entry ██▓
█▓█ modes for conditional probability distribution: ██▓
█▓█ probabilistic, deterministic and equation ██▓
█▓█ + powerful formula ██▓
█▓█ editor with a complete function and operator ██▓
█▓█ library (discrete & continuous probability ██▓
█▓█ distributions, arithmetic and trigonometric ██▓
█▓█ functions, ...) ██▓
█▓█ + table completion ██▓
█▓█ and normalization tools, cut & paste between ██▓
█▓█ tables and external applications ██▓
█▓█ o Constraint nodes to ██▓
█▓█ express constraint that hold between nodes ██▓
█▓█ o Enhanced traceability and ██▓
█▓█ documentation thanks to hypertext comments ██▓
█▓█ associated to the graph, the nodes and the ██▓
█▓█ arcs ██▓
█▓█ o Color node and arc ██▓
█▓█ tagging to semantically group your variables and ██▓
█▓█ probabilistic relations ██▓
█▓█ * Automatic learning or updating of ██▓
█▓█ your models from your data (text files and ██▓
█▓█ databases) ██▓
█▓█ o Learning conditional ██▓
█▓█ probabilities for a given network ██▓
█▓█ o Discovering of all the ██▓
█▓█ probabilistic relations that hold in your data ██▓
█▓█ base (Association discovery) ██▓
█▓█ o Supervised learning ██▓
█▓█ entirely devoted to characterizing a target ██▓
█▓█ variable ██▓
█▓█ o Selection of the minimal ██▓
█▓█ subset of variables correlated to the target ██▓
█▓█ variable ██▓
█▓█ o Bayesian Clustering to ██▓
█▓█ invent new concepts ██▓
█▓█ o Robust Missing value ██▓
█▓█ processing ██▓
█▓█ o Validation tools qualifying ██▓
█▓█ the obtained models (confusion matrix, lift and ██▓
█▓█ Roc curves) ██▓
█▓█ * Quickly assimilate the represented ██▓
█▓█ knowledge using a set of original analytical ██▓
█▓█ tools ██▓
█▓█ o Strength of the ██▓
█▓█ probabilistic relations (arc's thickness and HTML ██▓
█▓█ report) ██▓
█▓█ o Amount of information ██▓
█▓█ brought to the target node/modality ██▓
█▓█ o Type of probabilistic ██▓
█▓█ relations ██▓
█▓█ o Complete HTML analysis ██▓
█▓█ report of the target variable ██▓
█▓█ o HTML report of the ██▓
█▓█ evidence set analysis ██▓
█▓█ o Causal analysis (essential ██▓
█▓█ graphs) ██▓
█▓█ o Automatic network layouting ██▓
█▓█ algorithms ██▓
█▓█ * Use the models in interactive or ██▓
█▓█ batch mode ██▓
█▓█ o Positive, negative and ██▓
█▓█ soft evidences on the variable states ██▓
█▓█ o Simulation of "What-if" ██▓
█▓█ scenarios with probability variation highlighting ██▓
█▓█ o Adaptive questionnaires ██▓
█▓█ taking into account Costs and Information Gains ██▓
█▓█ o Off-line Tagging of new ██▓
█▓█ cases contained in a file ██▓
█▓█ o Robust imputation algorithm ██▓
█▓█ to complete data with missing values ██▓
█▓█ * Introduce the temporal dimension into ██▓
█▓█ your models ██▓
█▓█ o Compact representation of ██▓
█▓█ Dynamic Bayesian networks ██▓
█▓█ o Time node for an explicit ██▓
█▓█ use of time in the equations ██▓
█▓█ o Temporal simulation step ██▓
█▓█ by step or by period with a graphical view of ██▓
█▓█ the probability evolution ██▓
█▓█ o Observations file to ██▓
█▓█ specify the context of the scenarios ██▓
█▓█ * Representation, evaluation and ██▓
█▓█ learning of your action policies ██▓
█▓█ o Decision nodes for ██▓
█▓█ modeling your actions ██▓
█▓█ o Quality tables associated ██▓
█▓█ to Decision nodes for a direct representation ██▓
█▓█ of action policies ██▓
█▓█ o Utility nodes to valuate ██▓
█▓█ the states and to associate cost/gains to node ██▓
█▓█ modalities ██▓
█▓█ o Reinforcement learning ██▓
█▓█ algorithms to automatically discover policies ██▓
█▓█ that optimize the expected sum of utilities ██▓
█▓█ * Complete interoperability ██▓
█▓█ o Connection with your ██▓
█▓█ databases by using JDBC/ODBC ██▓
█▓█ o SQL Interface ██▓
█▓█ o Exportation of Bayesian ██▓
█▓█ networks, tables, equations, graphs, matrices and ██▓
█▓█ reports by using simple copy&paste, as images, ██▓
█▓█ numerical data and HTML texts ██▓
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▀██▓▄▄ ▐██▄ ▄ Install Notes ▄ ▄█▓▌ ▄▄▓██▀
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█▓█ 1. Unpack the pre-cracked software ██▓
█▓█ 2. Use the following serials to register ██▓
█▓█ ██▓
█▓█ 10A3-9A30-6473-04B8 ██▓
█▓█ ██▓
█▓█ 45B3-3JKU-5283-FSGU ██▓
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▐█▓▌ ▄██▄ ▄▄█▓▄▄ ▄▄▀▀ ■ ■ ▀▀▄▄ ▄▄██▓▄ ▄██▄ ▐█▓▌
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▄ ▄▄▄█ Greets to all who work hard to make the scene █▄▄▄ ▄
▄█▓ █▓▌ ▐█▓ █▓▄
█▓▌ ▐█▓ secure and enjoyable for everyone! █▓▌ ▐█▓
▀█▓ █▓▌ ▐█▓ █▓▀
▀▀▄ █▓▌ Some general notes... ▐█▓ ▄▀▀
▐█▓ █▓▌
██▓ █ - we dont want our releases spread via usenet,ftp █ ██▓
▐█▓ ▐█ - we dont want our releases being listed on ▓▌ █▓▌
█▓ █▓ several public dupe-sites like nforce ██▓ █▓
█▓ █▓▓ - we dont want to see our releases on public places ██▓ █▓
▄█▓ ▄█▓▓ - nor do we support one of these points ██▓▄ █▓▄
▐█▓▌ ██▓▓ ██▓▓ ▐█▓▌
▐██▓ ██▓▀ Think about it and try to make the scene as secure... ▀██▓ ██▓▓
▀███▄▄▄░ ... as possible ░▄▄▄█▓▓▀
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▐▓▌ Ascii by Yce*Remorse ▐▓▌
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FILE_ID.DIZ
DIGERATI presents keygen for BayesiaLab v3.3 |