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Neural Net Lottery Picker

677 replies. Last post 9 days ago by dr san.

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Lyon
France
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December 17, 2012
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Posted: August 20, 2016, 4:52 pm - IP Logged

once more 1 +1 only

the result was

10-15-28-35-43

i will see some other settings.....by Monday.

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    Krakow
    Poland
    Member #86302
    February 2, 2010
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    Posted: August 26, 2016, 2:56 am - IP Logged

    That's the settings I use for my 6/49 game and think to be the best. I use 3 training ranges( 33, 35 and 37 draws) and limit the number of generated lines to 5 only for each range. Most of the times you can find 4-5 correct numbers among them. Special attention should be paid to the first number as it can be up to 2 +/-.

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      Krakow
      Poland
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      February 2, 2010
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      Posted: August 26, 2016, 3:43 am - IP Logged

      Here's an example :

      The winning numbers were :

      07,08,34,35,37,48

       

      06-10-18-26-35-42-
      06-09-17-27-34-41-
      07-08-16-28-37-43-
      06-11-15-29-36-44-
      06-12-14-25-38-45-
      04-10-16-26-35-45-
      06-11-17-27-34-43-
      06-09-18-25-36-42-
      06-12-19-24-33-44-
      06-08-20-28-32-46-
      06-10-17-26-35-44-
      06-09-18-27-36-43-
      06-11-19-28-34-42-
      01-12-20-25-37-41-
      03-08-21-29-33-45-

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        United States
        Member #139779
        March 3, 2013
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        Posted: August 29, 2016, 9:26 am - IP Logged

        Here's an example :

        The winning numbers were :

        07,08,34,35,37,48

         

        06-10-18-26-35-42-
        06-09-17-27-34-41-
        07-08-16-28-37-43-
        06-11-15-29-36-44-
        06-12-14-25-38-45-
        04-10-16-26-35-45-
        06-11-17-27-34-43-
        06-09-18-25-36-42-
        06-12-19-24-33-44-
        06-08-20-28-32-46-
        06-10-17-26-35-44-
        06-09-18-27-36-43-
        06-11-19-28-34-42-
        01-12-20-25-37-41-
        03-08-21-29-33-45-

        Got an idea... When looking at NNLP to make a straight guess/ find number patterns in a 6/49 game seems to be alot of mathematical heavy lifting with a huge number of possible numbers. Would it be easier for NNLP to predict something with a higher frequency of repeating, like sums? Just an idea but according to Gail Howards most probable sums page, the most common sums are between 113-181 for a 6/49 game thats 68 3 digit numbers. I would make a spreadsheet of the past winning sums, using the sums in NNLP to predict the next sum since they have a much higher chance of repeating. Try to play straight numbers picked by NNLP that sum up to the predicted sums. Just an idea hope it helps or sparks a better idea with someone else.

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          Posted: August 29, 2016, 11:07 am - IP Logged

          All of the screen shots / screen caps of the various settings in the Neural Net Lottery Picker (NNLP v. 2.1) are now missing from this forum.  Did anyone save them?

           

          I would like to have copies.

           

          Thanks.

           

           

          Kosh

          I think you were,asking about Learning rate, and Momentum in a previous post. I found this very interesting but some what technical article that may give an idea of what to do in NNLP .

          https://en.wikibooks.org/wiki/Artificial_Neural_Networks/Neural_Network_Basics

          Hope it helps.

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            greenville, sc
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            Posted: August 29, 2016, 9:35 pm - IP Logged

            Just asking if there is still a link to the .txt files for state lottery.  i searched and located

            the one post but link is not valid.  Thanks

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              Posted: August 31, 2016, 12:50 am - IP Logged

              Just asking if there is still a link to the .txt files for state lottery.  i searched and located

              the one post but link is not valid.  Thanks

              So you will know how the draws need to be like (?), maybe, I think, at least that is how they were "posted".

              This is a short sample:

              5-13-15-22-27
              1-8-17-19-23
              2-9-13-17-34
              9-16-18-20-26
              1-5-17-23-30
              8-17-20-27-34
              3-9-16-21-31
              7-14-16-20-22
              1-4-7-27-28
              17-21-28-33-36
              3-7-10-27-38
              12-23-35-36-37
              4-17-19-23-30
              10-30-31-32-36
              14-22-30-31-38
              2-3-5-24-33
              2-4-6-15-22
              6-24-26-31-36
              5-9-29-34-35
              4-6-21-23-34
              2-11-15-18-37
              3-9-15-27-37
              8-10-14-19-31
              5-6-16-17-28
              9-12-24-30-32
              8-15-17-23-38
              1-6-30-34-38
              4-21-29-32-38
              1-7-18-28-33
              8-17-20-34-38

              And this is another short sample:

              4-3-3
              6-6-6
              5-5-2
              1-3-6
              0-9-5
              4-2-8
              7-9-4
              4-1-4
              5-5-7
              5-8-6
              5-9-5
              2-7-4
              8-6-6
              9-4-2
              6-1-9
              8-3-5
              6-5-6
              6-3-7
              5-4-5
              0-2-4
              7-2-2
              5-8-9
              4-6-7
              6-0-8
              1-6-3
              0-4-0
              8-4-8
              1-7-0
              1-4-8
              5-2-6

              And one last short sample:

              3-2-7-1
              6-1-3-1
              7-7-2-7
              2-2-2-1
              2-6-2-0
              7-0-3-7
              7-6-4-0
              3-8-4-4
              5-6-0-4
              6-2-5-8
              6-5-2-5
              8-9-2-2
              7-2-6-6
              7-6-1-4
              7-6-9-5
              3-6-5-3
              7-7-9-6
              2-8-9-9
              5-4-6-9
              7-5-9-5
              4-4-5-0
              7-3-4-8
              6-4-7-6
              8-8-2-2
              4-2-6-1
              1-3-9-5
              5-8-9-7
              9-3-3-6
              7-1-9-8
              9-3-4-8

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                Posted: September 2, 2016, 7:29 pm - IP Logged

                All of the screen shots / screen caps of the various settings in the Neural Net Lottery Picker (NNLP v. 2.1) are now missing from this forum.  Did anyone save them?

                 

                I would like to have copies.

                 

                Thanks.

                 

                 

                Kosh

                I would like to amend my original question since it was not clear.

                 

                What I meant to say was that all of the screen shots / screen caps of the various settings in the Neural Net Lottery Picker software (NNLP v 2.1) that were originally posted by Stoopendaal are now missing from this forum.  As an example, observe all the blank, empty white spaces in the post Stoopendaal made on page 2 of this forum where the screen shots / screen caps used to be.   The post in question is dated August 12, 2015 at 4:41 a.m.   The post is at the top of page 2.

                 

                Did anyone save any screen shots or screen caps of all the screen shots and screen caps that Stoopendaal has since removed from his posts?

                 

                I would like to have copies.  Please let me know.  Thanks.

                 

                Sincerely,

                 

                Kosh

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                  Posted: September 2, 2016, 8:03 pm - IP Logged

                  MW, try following settings :

                  05-08-17-24-37-44-;12,3929044970288;0,612815274382113;0,219650652835587;16:03:07.5431528;Learning Rate:0,0192| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  05-07-18-25-36-45-;12,2329451409627;0,608847523852977;0,210849514552098;16:03:08.9650306;Learning Rate:0,0192| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;2-)
                  04-09-19-26-38-43-;12,1434674087449;0,606616733095172;0,207347696357373;16:03:34.5432073;Learning Rate:0,0192| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  05-08-17-23-37-44-;14,5761832110259;0,66460704295564;0,232426332580341;16:04:11.5589127;Learning Rate:0,017067| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  05-08-18-23-36-44-;12,336940638186;0,611430033614343;0,214044260444525;16:04:37.8245994;Learning Rate:0,017067| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  05-09-17-24-37-43-;12,158807610587;0,606999765627905;0,218647854143968;16:04:39.2464729;Learning Rate:0,017067| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  04-10-16-22-38-45-;11,9047850774904;0,600625559691107;0,239013818590761;16:04:52.0902559;Learning Rate:0,017067| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;0-)
                  05-08-17-24-37-44-;11,8299026484079;0,59873357884505;0,209510490414856;16:05:25.1996982;Learning Rate:0,014935| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  05-07-18-25-36-45-;11,484387815926;0,58992520881698;0,19387289802022;16:05:28.0590839;Learning Rate:0,014935| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;2-)
                  05-06-19-23-35-43-;11,3966185205304;0,587666637116409;0,194271855338321;16:06:10.7623016;Learning Rate:0,014935| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;2-)
                  05-08-17-24-37-44-;12,0383319854959;0,603985048618275;0,188781262932607;16:06:32.5592197;Learning Rate:0,012803| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  05-09-18-23-36-43-;11,7533751674402;0,596793836983782;0,199210897903377;16:06:39.6998607;Learning Rate:0,012803| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;1-)
                  05-07-19-25-35-45-;11,397915151742;0,587700066559981;0,206960887888588;16:06:46.8405009;Learning Rate:0,012803| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:33;3-)

                  The actual winning numbers were : 5, 7, 19, 41, 46, 49

                  Dear adamcustom:

                   

                  What do you mean by Test Data Range which you give as 33;1- or 33;2- or 33;0-, etc.?

                   

                  Sincerely,

                   

                  Kosh

                    MillionsWanted's avatar - 24Qa6LT

                    Norway
                    Member #9517
                    December 10, 2004
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                    Posted: September 4, 2016, 6:28 am - IP Logged

                    For anyone having problems with their antivirus giving false positives. Avast antivirus allows you to whitelist folders and files.

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                      Krakow
                      Poland
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                      Posted: September 4, 2016, 8:57 am - IP Logged

                      Dear adamcustom:

                       

                      What do you mean by Test Data Range which you give as 33;1- or 33;2- or 33;0-, etc.?

                       

                      Sincerely,

                       

                      Kosh

                      Kosh

                      It gives you the number of hits given the parameteres when backtesting. In this case against the most recent draw.

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                        Krakow
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                        Posted: September 5, 2016, 2:53 pm - IP Logged

                        You might as well try these settings :

                        02-08-20-48-47-49-;21,1183045415693;1,0028128188244;2,11966062328724;20:20:41.9306152;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;4-)
                        02-10-12-48-49-47-;21,5788466613317;1,0136883775254;2,33342749391307;20:20:47.5087466;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                        02-08-20-48-47-46-;29,0584631840539;1,17632323028061;2,26692314884001;20:20:53.1025101;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                        02-10-24-48-47-49-;27,7298038364091;1,14911568144935;2,39122906118984;20:20:58.6962665;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                        02-07-06-46-45-44-;25,513433005764;1,10223653596987;2,33900397908347;20:21:01.4775212;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                        02-08-21-47-48-49-;29,7253767330616;1,18974540559978;2,17933740598399;20:21:15.4306705;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                        02-06-22-48-47-49-;25,093379235453;1,09312525391002;2,41306573436489;20:21:20.9931851;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                        03-08-25-48-47-46-;22,5811790817696;1,03696395404519;2,19481617948232;20:21:26.5713204;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;1-)
                        02-14-22-45-44-43-;22,6451491725231;1,03843171984816;2,11201955897521;20:21:30.7275734;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                        02-14-07-48-47-49-;25,4576366118837;1,10103061269417;2,23778150864817;20:21:32.1338264;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)

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                          Posted: September 5, 2016, 4:07 pm - IP Logged

                          You might as well try these settings :

                          02-08-20-48-47-49-;21,1183045415693;1,0028128188244;2,11966062328724;20:20:41.9306152;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;4-)
                          02-10-12-48-49-47-;21,5788466613317;1,0136883775254;2,33342749391307;20:20:47.5087466;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                          02-08-20-48-47-46-;29,0584631840539;1,17632323028061;2,26692314884001;20:20:53.1025101;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                          02-10-24-48-47-49-;27,7298038364091;1,14911568144935;2,39122906118984;20:20:58.6962665;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                          02-07-06-46-45-44-;25,513433005764;1,10223653596987;2,33900397908347;20:21:01.4775212;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                          02-08-21-47-48-49-;29,7253767330616;1,18974540559978;2,17933740598399;20:21:15.4306705;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                          02-06-22-48-47-49-;25,093379235453;1,09312525391002;2,41306573436489;20:21:20.9931851;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                          03-08-25-48-47-46-;22,5811790817696;1,03696395404519;2,19481617948232;20:21:26.5713204;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;1-)
                          02-14-22-45-44-43-;22,6451491725231;1,03843171984816;2,11201955897521;20:21:30.7275734;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                          02-14-07-48-47-49-;25,4576366118837;1,10103061269417;2,23778150864817;20:21:32.1338264;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)

                          Have noticed a little pickup with this one.

                          ;Learning Rate:0.03| Noise:0.001|Threshold Error:0|Hidden Neurons:8|

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                            Krakow
                            Poland
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                            Posted: September 6, 2016, 6:41 am - IP Logged

                            Have noticed a little pickup with this one.

                            ;Learning Rate:0.03| Noise:0.001|Threshold Error:0|Hidden Neurons:8|

                            For my game it's hard to find settings that work worse than yours. Hardly one number hit per line and that every 3 lines or so. They would be good to eliminate combinations instead of playing them

                            While my settings give pretty good results :

                            02-10-13-48-47-49-;21,5723717704877;1,01353628380766;2,21433322736329;12:36:40.2132324;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                            02-10-20-48-47-46-;30,1942540979571;1,19909199968653;2,46692058144113;12:36:45.7913630;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                            02-06-18-45-44-43-;27,9005308840133;1,1526476949886;2,3779936335269;12:36:47.1819910;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                            02-08-22-42-41-49-;25,6190457680689;1,10451553197962;2,33958816471062;12:36:48.5726229;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                            02-13-11-48-49-47-;25,7802883115949;1,10798590999282;2,40115315319038;12:36:51.3694980;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)
                            02-09-20-47-48-49-;23,7208222018167;1,062808996006;2,03064935634615;12:36:56.9163836;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;4-)
                            03-09-07-48-49-47-;24,2310352156669;1,07417820672068;2,38663099467343;12:37:02.4788971;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                            02-11-13-44-43-42-;23,7414655391961;1,06327135673682;2,51282952777427;12:37:06.6507806;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                            03-08-15-48-49-47-;23,4690701518972;1,05715408959052;2,30171476878691;12:37:08.0570285;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;2-)
                            02-09-10-48-49-47-;25,1012932043424;1,09329761565516;2,27436694411517;12:37:13.6039137;Learning Rate:0,140734| Noise:0,24|Threshold Error:0,1|Hidden Neurons:200|Test Data Range:21;3-)

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                              Member #98539
                              October 9, 2010
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                              Posted: September 27, 2016, 11:38 am - IP Logged

                              To All:

                               

                              There have been a number of posts on this thread to the effect that the software program Neural Net Lottery Picker  (NNLP v. 2.1) has been tripping various anti virus programs. 

                               

                              Has anyone thought to hire a company or software programmer to deobfuscate the software and reverse engineer the software program to confirm whether or not there is a malware program, trojan, or virus hidden or embedded within this software program?

                               

                              I do not think that this should be too difficult since the total file size of this software program is only 214 KB.

                               

                              There should be some red flags to look for such as the presence of assembly code, for example. 

                               

                              Sincerely,

                               

                              Kosh

                                 
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