Fix typos

ClassImp is a macro defined in Rtypes.h. It can be written without trailing
semicolon. However, clang-format is based on lexing and it doesn't know at
all about preprocessors and how to expand macros. When visiting ClassImp(X)
it thinks this is not a completed entity (as it doesn't expand macros) and
considers the next line as continuation of the previous.

Inserting a semicolon fixes the issue and makes formatting with clang-format
in the ROOT codebase less tricky.

This correctly causes a compilation error when doing for example
TMatrixD M(2,2); M[1,0] = 2;

Add also possibility to initialise TMatrixDROw with an initialiser list. So one can do
M[1] = {1,2};

Use TFormulaOld in MLP

a TFormula was created in a loop w/o freeing the memory.
It was noticeable in complex neaural nets.

The attached patchset fixes a bunch of typo in the source:
0001-succes-success.patch
0002-preceed-preced.patch
0003-informations-information.patch
0004-childs-children.patch
0005-avaliable-available.patch
0006-writeable-writable.patch
0007-comand-command.patch
0008-unkown-unknown.patch
0009-wierd-weird.patch
0010-wheter-whether.patch
0011-unecessary-unnecessary.patch
0012-splitted-split.patch
0013-registerd-registered.patch
0014-recieve-receive.patch
0015-processsing-processing.patch
0016-ouput-output.patch
0017-mutiple-multiple.patch
0018-lenght-length.patch
0019-interupted-interrupted.patch
0020-independant-independent.patch
0021-inconsistant-inconsistent.patch
0022-expresion-expression.patch
0023-explicitely-explicitly.patch
0024-enviroment-environment.patch
0025-deafult-default.patch
0026-continous-continuous.patch
0027-completly-completely.patch
0028-commited-committed.patch
0029-choosen-chosen.patch
0030-backgroud-background.patch
0031-auxilliary-auxiliary.patch
0032-authentification-authentication.patch
0033-appropiate-appropriate.patch
0034-an-other-another.patch
0035-environement-environment.patch
0036-targetting-targeting.patch
0037-suppported-supported.patch
0038-paramater-parameter.patch


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  using namespace std;
from Riostream.h, which has huge consequences for all of ROOT.
Riostream.h is now a simple wrapper for fstream, iostream, iomanip for backward compatibility; Riosfwd.h simply wraps iosfwd.

Because of templates and their inline functions, Riostream.h needed to be included in headers, too (e.g. TParameter.h), which violated the assumption that Riostream.h is not exposing its using namespace std to headers.
ROOT now requires R__ANSISTREAM, R__SSTREAM, which does not change the set of supported compilers.

Without "using namespace std", several identifiers are now prefixed by std::; e.g. roofit/* source files now have a using namespace std to keep their coding style.
TFile::MakeProject() now generates "using namespace std" to convert the CINT-style class names into C++ ones.


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change TMultiLayerPerceptron::LoadWeights and DumpWeights to return a Bool_t to flag an error with the input file

see https://savannah.cern.ch/bugs/?89796


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Added a third parameter to set the limit, and the behavior is then controled 
by extra options.
// - "minErrorTrain" (stop when NN error on the training sample gets below 
minE
// - "minErrorTest" (stop when NN error on the test sample gets below minE

The limit on epochs is always active but can be put to a high value. This 
guaranties the stopping condition.


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and Printf().


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This patch fixes the spelling of "function" in the root source code
and documentation, which is misspelled (sometimes as part of larger
"function"-based words) at least 152 times:

* "funciton" 48 times
* "funcion" 36 times
* "funtion" 23 times
* "fucntion" 17 times
* "functionn" 6 times
* "fuction" 6 times
* "fuunction" 4 times
* "functioin" 3 times
* "fonction" 3 times
* "funstion" twice
* "fnuction" once
* "functiom" once
* "functio" once
* "funcition" once


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 Hidden layers don't have names, so complain (instead of crashing) if they do. Reduce code duplication.


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Add a new method in the C++ exported NN function that takes an array as input.


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   mathcore
   mathmore
   fftw
   foam
   fumili
   genvector
   matrix
   minuit
   minuit2
   mlp
   physics
   smatrix
   splot
   unuran
   quadp


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ROOT can not be compiled with gcc-4.3.
Some ROOT source files doesn't contain required #include directives,
for example, they use strlen(), but #include <string.h> is missed or
malloc() is used and #include <stdlib.h> is missed. 

Earlier versions of gcc allowed some headers to be included implicitly,
but issued a warning (-Wimplicit-function-declaration). Newer one,
gcc-4.3 denies such silly behaviour: all required headers must be explicitly
included. 

Attached patch fixes this. Also it fixes another issue, which disallows
ROOT to compile under gcc-4.3: C functions don't belong to namespace std,
so expressions like std::memcpy() are no longer valid and plain memcpy()
should be used instead.


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are separated by semicolons". In fact they are separated by colons ":".
see:  <http://savannah.cern.ch/bugs/?31248>


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Fix for problem reported at:  http://root.cern.ch/phpBB2/viewtopic.php?t=5396


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When I moved BFGS matrices into the BFGS specific code, I overlooked the fact
that matrices are not to be reinitialized at each step of the loop.
The consequence is that BFGS training is far from optimal from release
v5-15-08, but other methods are not affected. Using MLP with ROOT
v5-15-08 -> v5-16-00  I recommend to use the
TMultiLayerPerceptron::kFletcherReeves learning method.


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"Moved the declaration of 3 matrices to the BFGS-specific part of the code to
avoid unneeded instantiations when using other training methods."


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-Remove unused references to TROOT.h


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   Fix a problem reported by Herbert Greenlee
The fortran-generated code was indeed
protected, but not the C++/python versions.

   Herbert Greelee said:
"Neural network code generated by TMultiLayerPerceptron contains code
 similar to the following in "neuron" methods:

    return ((1/(1+exp(-input)))*1)+0;

 This code is vulnerable to floating point overflows for moderately large
 negative values of "input."  The mathematical function itself is well
 defined for all values of input.  This is a computer arithmetic problem.
 A better computer science implementation of this function is needed that
 avoids floating point overflows in the intermediate results."


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Add a few more comments explaining the difference/enhancements between
the original MLPFIT package and TMultiLayerPerceptron.


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Assert   ->  R__ASSERT
Check    ->  R__CHECK
Change the TCollection.h macro:
ForEach  ->  R__FOR_EACH
This to avoid potential problems due too trivial macro names.
The old macros will be removed in the next release. Currently
they will print out warning messages with the advice to move
to the new macro names.


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