From: aminer68@gmail.com   
      
   Hello,   
      
      
   More of my philosophy about non-linear regression and about logic and about   
   technology and more of my thoughts..   
      
   I am a white arab from Morocco, and i think i am smart since i have also   
   invented many scalable algorithms and algorithms..   
      
      
      
   I think i am highly smart since I have passed two certified IQ tests and i   
   have scored "above" 115 IQ, and i mean that it is "above" , so i think that   
   R-squared is invalid for non-linear regression, but i think that something   
   that look like R-squared for    
   non-linear regression is to use Relative standard error that is the standard   
   deviation of the mean of the sample divide by the Estimate that is the mean of   
   the sample, but if you calculate just the standard error of the estimate (Mean   
   Square Error), it    
   is not sufficient since you have to know what is the size of the standard   
   error of the estimate relatively to the curve and its axes, so read my   
   following thoughts so that to understand more:   
      
      
   So the R-squared is invalid for non-linear regression, so you have to use the   
   standard error of the estimate (Mean Square Error), and of course you have to   
   calculate the Relative standard error that is the standard deviation of the   
   mean of the sample    
   divide by the Estimate that is the mean of the sample, and i think that the   
   Relative standard Error is an important thing that brings more quality to the   
   statistical calculations, and i will now talk to you more about my interesting   
   software project for    
   mathematics, so my new software project uses artificial intelligence to   
   implement a generalized way with artificial intelligence using the software   
   that permit to solve the non-linear "multiple" regression, and it is much more   
   powerful than  Levenberg–   
   Marquardt algorithm , since i am implementing a smart algorithm using   
   artificial intelligence that permits to avoid premature    
   convergence, and it is also one of the most important thing, and    
   it will also be much more scalable using multicores so that to search with   
   artificial intelligence much faster the global optimum, so i am    
   doing it this way so that to be professional and i will give you a tutorial   
   that explains my algorithms that uses artificial intelligence so that you   
   learn from them, and of course it will automatically calculate the above   
   Standard error of the estimate    
   and the Relative standard Error.   
      
   More of my philosophy about non-linear regression and more..   
      
   I think i am really smart, and i have also just finished quickly the software   
   implementation of Levenberg–Marquardt algorithm and of the Simplex algorithm   
   to solve non-linear least squares problems, and i will soon implement a   
   generalized way with    
   artificial intelligence using the software that permit to solve the non-linear   
   "multiple" regression, but i have also noticed that in mathematics you have to   
   take care of the variability of the y in non-linear least squares problems so   
   that to    
   approximate, also the Levenberg–Marquardt algorithm (LMA or just LM) that i   
   have just implemented , also known as the damped least-squares (DLS) method,   
   is used to solve non-linear least squares problems. These minimization   
   problems arise especially in    
   least squares curve fitting. The Levenberg–Marquardt algorithm is used in   
   many software applications for solving generic curve-fitting problems. The   
   Levenberg–Marquardt algorithm was found to be an efficient, fast and robust   
   method which also has a    
   good global convergence property. For these reasons, It has been incorporated   
   into many good commercial packages performing non-linear regression. But my   
   way of implementing the non-linear "multiple" regression in the software will   
   be much more powerful    
   than Levenberg–Marquardt algorithm, and of course i will share with you many   
   parts of my software project, so stay tuned !   
      
      
   More of my philosophy about the truth table of the logical implication and   
   about automation and about artificial intelligence and more of my thoughts..   
      
      
   I think i am highly smart since I have passed two certified IQ tests and i   
   have scored "above" 115 IQ,  and i mean that it is "above",  and now    
   i will ask a philosophical question of:   
      
   What is a logical implication in mathematics ?   
      
   So i think i have to discover patterns with my fluid intelligence    
   in the following truth table of the logical implication:   
      
   p q  p -> q   
   0 0    1   
   0 1    1   
   1 0    0   
   1 1    1   
      
   Note that p and q are logical variables and the symbol -> is the logical   
   implication.   
      
   And here are the patterns that i am discovering with my fluid intelligence   
   that permit to understand the logical implication in mathematics:   
      
   So notice in the above truth table of the logical implication    
   that p equal 0 can imply both q equal 0 and q equal 1, so for    
   example it can model the following cases in reality:   
      
   If it doesn't rain , so it can be that you can take or not your umbrella, so   
   the pattern is that you can take your umbrella since    
   it can be that another logical variable can be that it can rain    
   in the future, so you have to take your umbrella, so as you    
   notice that it permits to model cases of the reality ,   
   and it is the same for the case in the above truth table of the implication of   
   if p equal 1, it imply that q equal 0 , since the implication is not   
   causation, but p equal 1 means for example    
   that it rains in the present, so even if there is another logical variable   
   that says that it will not rain in the future, so you have    
   to take your umbrella, and it is why in the above truth table    
   p equal 1 imply q equal 1 is false, so then of course i say that    
   the truth table of the implication permits to model the case of causation, and   
   it is why it is working.   
      
   More of my philosophy about objective truth and subjective truth and more of   
   my thoughts..   
      
   Today i will use my fluid intelligence so that to explain more    
   the way of logic, and i will discover patterns with my fluid intelligence so   
   that to explain the way of logic, so i will start by asking the following   
   philosophical question:   
      
   What is objective truth and what is subjective truth ?   
      
   So for example when we look at the the following equality: a + a = 2*a,    
      
   [continued in next message]   
      
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