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3.1 Step 1: Input File Format3.1.1 Comment Section  Part 1 of the Input File3.2 Step 2 and 3: Link and Run Chapter 2 is the quick version of the manual. Chapter 3 and 4 will present a detailed user's guide. The operation has two phases:
Your Raw Data  90% of the work
The best way to learn the input file format is to look at the examples in the PredictorPro, for example, click "Example/Intel 2". The format is very easy to learn. The input file must be prepared in the text file format. The PredictorPro has its own text editor. Or if you wish, you can use any word processor, like Microsoft Word, or WordPerfect; just make sure you save the data file in the text format. The input file has three sections:
The comment section starts with a “*” and ends with another “*”. The purpose of this section is to document your data:
*Note: the PredictorPro will ignore this section. This section is for your remarks only. 3.1.2 Number of variables  Part 2 of the Input File This section has a single integer, which will tell the PredictorPro how many variables you will use. Example: In the Intel example in the last chapter, there was only one variable, therefore, the number of variables is 1. If you have 2 variables, then the number of variables is 2, ...
This section contains the data. Example Considering the Intel example, which we showed
you earlier. This example can be generated by clicking "Example/Intel 2".
Note that it has three sections: comment, the number of variables, and
the data:
*
The operation of the Predictor is “link and run”. There are two methods of doing this. The first one deals with one or a few predictions. The second one deals with repeatedly making predictions from one data file. Method 1:
You can check the linking by clicking the inputbutton (5th button).
Link:
This method is a better one if you repeatedly make predictions from one data file. For example, your Excel data file has 10 columns and you want to make a prediction with each column. Method 1 requires you to create 10 new files, which makes data management difficult. Using Method 2, you can cut and paste one column into the PredictorPro, save the file and make a prediction; then repeat it for each column. In the end, you still have just one data file. The basic commends are:
Real+ Linear
The Linear mode deals with two situations:
Example Lottery numbers are good examples where the numbers are in a fixed interval. Intel stock is a typical example of the exponential mode. In this section, we will introduce the rest of the commands. Real + Linear basic command
Figure 7. The "Integer" Commands
Integer + LinearSimilar to "Real/+ Linear" but uses integers. LinearSimilar to "Real/+ Linear" but uses integers.0 LinearSimilar to "Real/+ Linear" but uses integers.+ EnumerativeSimilar to "Real/+ Linear Enumerative" but uses integers. EnumerativeSimilar to "Real/ Linear Enumerative" but uses integers.0 EnumerativeSimilar to "Real/0 Linear Enumerative" but uses integers. Figure 8. The "Avg/Max" Commands
Avg/Max + Real LinearSimilar to "Real/+ Linear" but only prints the weighted average, most probable outcome, and the error. Real LinearSimilar to "Real/ Linear" but only prints the weighted average, most probable outcome, and the error.0 Real LinearSimilar to "Real/0 Linear" but only prints the weighted average, most probable outcome, and the error.+ Real ExponentialSimilar to "Real/+ Exponential" but only prints the weighted average, most probable outcome, and the error. Real ExponentialSimilar to "Real/ Exponential" but only prints the weighted average, most probable outcome, and the error.0 Real ExponentialSimilar to "Real/0 Exponential" but only prints the weighted average, most probable outcome, and the error.+ Integer LinearSimilar to "Integer/+ Linear" but only prints the weighted average, most probable outcome, and the error. Integer LinearSimilar to "Integer/ Linear" but only prints the weighted average, most probable outcome, and the error.0 Integer LinearSimilar to "Integer/0 Linear" but only prints the weighted average, most probable outcome, and the error.+ Integer EnumerativeSimilar to "Integer/+ Linear Enumerative" but only prints the weighted average, most probable outcome, and the error. Integer EnumerativeSimilar to "Integer/ Linear Enumerative" but only prints the weighted average, most probable outcome, and the error.0 Integer EnumerativeSimilar to "Integer/0 Linear Enumerative" but only prints the weighted average, most probable outcome, and the error. Figure 9. The "3Average" Commands
3Average and 10Average
+ Real LinearSimilar to "Real/+ Linear". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers. Real LinearSimilar to "Real/ Linear". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers.0 Real LinearSimilar to "Real/0 Linear". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers.+ Real ExponentialSimilar to "Real/+ Exponential". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers. Real ExponentialSimilar to "Real/ Exponential". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers.0 Real ExponentialSimilar to "Real/0 Exponential". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers.+ Integer LinearSimilar to "Integer/+ Linear". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers. Integer LinearSimilar to "Integer/ Linear". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers.0 Integer LinearSimilar to "Integer/0 Linear". This command will make 3/10 predictions down the line; each time it will use the weightedaverage(s) to calculate the next row of numbers. The default output file name is example2b.txt. You can change the output file name by clicking: “Data/Link”, or its button on the toolbar, then type in your new data file name. The "Real" and the "Integer" commands will have the following output format:
Example Intel 2. 1. Click "Example/Intel 2" to link the data to the PredictorPro. The input file will be opened at this point. 2. Click "Real/ Exponential" and the output below will be displayed: =================== Beginning =====================
3.5.1 Relative Probability or Rating Relative probability or rating is the ranking of the predicted numbers. This number is similar to an Internet Search Engine ranking number. PredictorPro presents you with rated possibilities: all possibilities and how valuable the PredictorPro thinks each one is via a relative probability. These ratings are relative probabilities. In the above example, ignoring results below 1000, the distribution is: Possibility Confidence*Probability
First of all, the predicted possibilities are 81.2484 ± 0.859271
where ± 0.859271 is the given error in the last line of the output file. Relative probabilities are proportional to probabilities. For example, let the relative probabilities be (3, 5), then they represent the probabilities (3/(3+5), 5/(3+5)) = (37.5%, 62,5%). The highest relative probability is called the Confidence Number. This number is given after the weightedaverage(s). The higher the number, the more confidence the PredictorPro has in that prediction. For each prediction, one Confidence Number is produced. In the above example, the confidence is 10,334. Unfortunately, no quantitative description can be made for the Confidence Number. You can get a feel for this Confidence Number from experience. However, it is vitally important for you to acquire a feel for gauging this number. You should ignore the prediction results all together if the confidence number is low, as shown above. Of course, you want the error as low as possible. This is not always
possible. The error is controlled by a userdefined variable, called Precision
level. The higher Precision level is, the lower the error will be.
We will discuss the Precision level in the next chapter.
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