How important in NeuralNet mathematics in research

How important in NeuralNet mathematics in research

Why Neural Net Is So Important When Conducting Astrological Research
By Alphee Lavoie, Ncgr Level IV

Neural Net mathematics is a exceptional tool to use in research. After creating a model with thousands astrological criteria, the criteria is sent to Air Software research program that compares your sample against control group and calculate the importance of each criteria. It will list all the criteria that are important which we call OFTEN as well as those considered not important which we call SELDOM according the chi-square and probability in mathematics. This list is then sent through the Neural Net mathematics. Neural Net will make sure that this list of criteria consistently indicates if it’s often or seldom important.
The following two graphs are the result of research that we’ve done to predicting winners in sports games. We tested different astrological techniques published in well-known astrology sport books. Through our research studies we found using these astrological techniques to predict winners were not dependable to predict winning outcomes. You can see from the graph below that Neural Net didn’t find it very clear if any of them happened often or seldom. The blue part of the graph indicates the strength of occurrence for Seldom and the red indicates the strength of occurrence for Often. The black portion of the graph refers to findings that are not important.

nnnotgood

Now if you compare this graph to the one below you will see the results of a breast cancer research that we’ve done is quite impressive. Notice how the results of seldom (blue) and the often (red) are spread away from the black part of the graph that shows not important at all. The further that the blue and red colors are from the center the stronger the often and seldom are for all these thousands astrological criteria used in the study.

nngood

Neural Net creates an artificial intelligence that you can use to check your results with other natal charts
Let’s take another look at the research for predicting sport events. Using the artificial intelligence model file that neural net created, we took over 9000 timed sporting events to see how well that they fit the model that was found in the research. This data was focused on predicting the winning teams when they played at home. In other words we input thousands of timed charts with locations of sport games where the team won at home.

fig1

As you can see the result wasn’t that great because the strength of each game was weak Indicated by the length of the bars.
Next, we checked games when the home team lost at home. After sending it through the artificial intelligence created by using the team winning at home, the results were not very different at all.

fig2

This indicates that all the astrological criteria that was important when the team won at home is not any different that when the team lost at home. That tells us that we cannot predict the outcome of sport events with any accuracy using these astrology techniques.

Now let’s take a look at some other research that produced some superior results. The next graph shows the our results from a research of breast cancer. We sent charts of people with breast cancer through the artificial intelligence file and the graph indicates that all of them would have breast cancer, and they did. This shows that the criteria that the research program found as being often the seldom happens were excellent. This is indicated by the length of the bars

cancer1

The next graph we uses the same artificial intelligence model that we used for individuals that had breast cancer. This time we sent through the charts of individuals with bone cancer. As you can see by the length of the bars that it didn’t have any of the same criteria that the breast cancer have. This a good indication that the research on breast cancer produced great results.

cancer2

Now if the bone cancer study would give the same results as the breast cancer study, That would tell us that the research did not find any important criteria that are explicitly to breast cancer. This is exciting, it proves that we can predict a woman having a high Probability of breast cancer in this lifetime with good accuracy.
Alphee