Predicting is making claims about something that will happen, often based on information from past and from current state.
Everyone solves the problem of prediction every day with various degrees of success. For example weather, harvest, energy consumption, movements of forex (foreign exchange) currency pairs or of shares of stocks, earthquakes, and a lot of other stuff needs to be predicted. ...
http://www.scriptol.com/programming/list-algorithms.php
http://www.ipedr.com/vol25/54-ICEME2011-N20032.pdf
http://www.brightpointinc.com/flexdemos/chartslicer/chartslicersample.html
http://blog.lookbackon.com/?page_id=2506
http://www.lookbackon.com/lab/LotteryPrediction/LotteryPrediction_AmCharts_R.swf http://www.lookbackon.com/lab/LotteryPrediction/LotteryPrediction_AmCharts_RCX.swf http://www.lookbackon.com/lab/LotteryPrediction/LotteryPrediction_FlexCharts.swf
Python data-mining and pattern recognition packages
Python Machine Learning Packages
Conference on 100 YEARS OF ALAN TURING AND 20 YEARS OF SLAIS
Python Multivarite Pattern Analysis
Neural Lotto — Lottery Drawing Predicting Method
1.A single variable:Shape and Distribution; ( Dot/Jitter plots,Histograms and Kernel Density Estimates,Cumulative Distribution Function,Rank-Order...)
2.Two variables:Establishing Relationships; ( Scatter plots,Conquering Noise,Logarithmic Plots,Banking...)
3.Time as a variable: Time-Series Analysis; (Smoothing,Correlation,Filters,Convolutions..)
4.More than two variables;Graphical Multivariate Analysis;(False-color Plots,Multi plots...)
5.Intermezzo:A Data Analysis Session;(Session,gnuplot..)
6...
1.Guesstimation and the back of envelope;
2.Models from scaling arguments;
3.Arguments from probability models;
4...
1.Simulations;
2.Find clusters;
3.Seeing the forest for the decision trees;
4....
1.Reporting, BI (Business Intelligence),Dashboard;
2.Financial calculations and modeling;
3.Predictive analytics;
4....
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Phase I.Graphics: Looking at Data;
1.A single variable:Shape and Distribution; ( Dot/Jitter plots,Histograms and Kernel Density Estimates,Cumulative Distribution Function,Rank-Order...)
2.Two variables:Establishing Relationships; ( Scatter plots,Conquering Noise,Logarithmic Plots,Banking...)
3.Time as a variable: Time-Series Analysis; (Smoothing,Correlation,Filters,Convolutions..)
4.More than two variables;Graphical Multivariate Analysis;(False-color Plots,Multi plots...)
5.Intermezzo:A Data Analysis Session;(Session,gnuplot..)
6...
Phase II.Analytics: Modeling Data;
1.Guesstimation and the back of envelope;
2.Models from scaling arguments;
3.Arguments from probability models;
4...
Phase III.Computation: Mining Data;
1.Simulations;
2.Find clusters;
3.Seeing the forest for the decision trees;
4....
Phase IV.Applications: Using Data;
1.Reporting, BI (Business Intelligence),Dashboard;
2.Financial calculations and modeling;
3.Predictive analytics;
4....
#TODO:
1.Using D3JS Chart to visualization the data; (http://techslides.com/over-1000-d3-js-examples-and-demos/);
2.Using Tableau software trail and error; (http://www.tableausoftware.com/)
3.Using PredictionIO API; (http://prediction.io)
4.Using Free Tempo-DB for time series database storage ; (https://tempo-db.com/docs/batch-import/python-script/)
5.Using BigML API; (https://bigml.com/)
6.Pandas+scikit+matplotlib+IPython Notebook; (http://nbviewer.ipython.org/url/www.onewinner.me/en/devoxxML.ipynb)
7.Implementing a highly scalable prediction; (http://www.slideshare.net/SpringCentral/implementing-a-highly-scalable-stock-prediction-system-with-r-apache-geode-and-spring-xd) (https://github.com/Pivotal-Open-Source-Hub/StockInference-Spark)