This is a neural network software, which simulates the function of a human brain. The software by itself cannot do anything. As a user, you are responsible to train this empty brain (linking your database to the DecisionMaker), after that, the software is ready to serve you as if it is one of your staff.
Making decisions based on your evaluation of the current situation is
a way of life:
*Examples based on real data are in the software.
In general, a decision is made based on several factors. Some of them
can be measured and have a historical track record. For example, a cancer
doctor orders a set of tests (see chapter 2) and the test results are represented
by numbers. If we train an intelligent machine with 100,000 cancer cases,
then the machine can be just as good as a cancer doctor in diagnosis, if
not better (see chapter 2).
Making decisions is a way of life in many businesses. Many corporations
already have their database in place that contains years of historical
data. It is often overwhelming because of the sheer volume to
mine the data for the purpose of strategic thinking, or simply to
make a daily decision.
This is where software can help you to make decisions based on your historical database. The software can learn years of experience from your database and use the knowledge to tell you what will happen if this were in the past. This provides you with a baseline for your decision making process. The software can learn years of experiences in seconds and is ready to serve you as if it is one of your staff.
Attrasoft DecisionMaker is a fast terabyte data processing tool for your database. Attrasoft DecisionMaker uses the data in a database to help you make business decisions. It does not matter what kind of database you have. What seems complicated to you, is not complicated to the Attrasoft DecisionMaker. After putting your data into the DecisionMaker, then in 2 clicks, suddenly your complicated problem will seem very simple.
90% of the work in using the DecisionMaker is to prepare your database containing your historical data. (Many corporations already have their database in place that contains years of historical data.)
10% of the remaining work is to operate the DecisionMaker (two clicks).
The DecisionMaker is especially good if you have a terabyte or gigabyte database because of its accuracy and speed.
The advantages of the Attrasoft DecisionMaker are:
Once your data is prepared correctly, the DecisionMaker is able
to provide you with rated predictions on any subject or any problem. Attrasoft
The Attrasoft DecisionMaker makes patterns out of complicated problems. The DecisionMaker is based on the neural network technology developed at Attrasoft. A neural net learns from past experience; this makes the neural software operation different from other software: you have to train the software first. You have to teach the DecisionMaker by showing it your historical data.
The software uses two files:
The software is a black box. The black box only has 1 parameter to setup plus 3 file names.
All you need to do is:
1.4 Step 1: Data Set and Data Collection
If you want the software for digital decisions, chances are you already have decided the "data set" and have collected volumes of data. This will make using the DecisionMaker very simple.
1.4.1 Data Set
Let us start from the beginning:
What are the factors for a stock? i.e. what is a data set for
a stock? There are hundreds of them:
An example of a data set for Intel stock is:
There are 10 variables here: the first 9 are obtained at the beginning
of one month; the question is: will the last variable be up or down?
In the training phase, the historical data of all 10 variables is collected and the software is trained. In the working phase, the values of the first 9 variables are provided, the software tells you the value of the last variable.
1.4.2 Data Collection
Once a data set is chosen, the next task is to collect data. For the stock market, some data can be collected free from the Internet.
The historical data for all 10 variables in the above example forms the stock-Database file. The values of the first 9 variables form your Question file. Both have to be fed into the DecisionMaker. The DecisionMaker learns from the stock-Database file, then looks at your questions and produces answers in the output file.
1.5 Step 2: Link
Once your historical data is all in one file and your questions are all in another file (step 1), these files are linked into the black box for training (step 2). In English, this means the DecisionMaker is learning your problem, your experience, and your values of your problem, starting from an empty but very smart brain. After that, the neural network black box is ready to make a prediction by clicking one command (step 3).
1.6 Step 3: Run
Once the link is completed, you need to click a prediction command ... the DecisionMaker will automatically provide you with all the possibilities and their respective probabilities ........ you have only clicked 2 buttons at this point ......... your complicated problem suddenly seems very simple.
The software is a black box. The black box only has 2 parameters to
The user's job is mainly in step 1: set up a data set and collect data,
if necessary, preprocess data.
The Attrasoft neural network is the based on the so-called Boltzmann machine neural network; this special type of neural network will predict a distribution, which is a set of rated possibilities. (This is similar to the Internet search engine: when you use a Internet search engine, you will get a set of rated possibilities.)
1.7 DecisionMaker's Sister
There are two types of predictions:
Order Predictor 2.6 when dealing with:
1.8 DecisionMaker's Version
The DecisionMaker has several versions:
Version Neurons prices
Standard version 65,000 $99.99
100K version 100,000 $499
250K version 250,000 $999
1M version 1,000,000 $9999
Other customized versions
$999 or up
If you need help on how to encode your problem, how to choose a data set, how to convert string data to numerical data, how to handle missing data, ..., the consulting fees are:
$250 per problem if the problem has 1000 rows or less;
$500 per problem if the problem has 1,001-10,000 rows or less;
$1000 per problem if the problem has more than 10,000 rows.