The odt file is actually made up of several text files, and git can support diff with some configuration. Step 1: In the GIT project I add the. gitattributes file with the following content: *.odt Diff=odtstep 2: Add the following paragraph to the. git/config file: [diff "odt"] binary = True Textco NV =/usr/local/bin/odt-to-txtstep 3: Create the/usr/local/bin/odt-to-txt file and add the following: #! /usr/bin/env perl# simplistic OpenDocument text (. odt) to plain text converter.# Author:philipp kempgenif (! defined ($ARG V[0]) {print STDERR "No filename given!\n"; Print STDERR "Usage: $ filename\n"; Exit 1;} my $content = "; open my $fh, '-| ', ' unzip ', '-qq ', '-P ', $ARGV [0], ' content.xml ' or Die $!; {Local $/= undef; # slurp Mode $content = < $fh;;} Close $fh; $_ = $content;s/<text:span\b[^>]*>//g; # remove spanss/<text:h\b[^>]*>/\n\n*****/g; # headerss/<text:list-item\b[^>]*>\s*<text:p\b[^>]*>/\n--/g; # list itemss/<text:list\b[^>]*>/\n\n/g; # listss/<text:p\b[^>]*>/\n/g; # paragraphss/<[^>]+>//g; # RemoveAll XML tagss/\n{2,}/\n\n/g; # remove multiple blank liness/\a\n+//; # Remove leading blank linesprint "\ n", $_, "\ n"; Step 4: Set File Execution permissions: chmod +x/usr/local/bin/odt-to-txt now use the diff command: sdf1/ ews/doc$ git diff f223a86348123b4cd682611f105ea0d4c9c8990f Intelligent Dispatch system. Odtdiff--git a/doc/Intelligent Dispatch system. ODT b/doc/ Intelligent dispatch System. Odtindex 96a6e29. b6fd443 100644---a/doc/intelligent dispatch system. odt+++ b/doc/Intelligent Dispatch system. odt@@ -1349,14 +1349,24 @@ kmeans cluster query with Kmeans clustering training, use ' K: Centroids can be light-the root node + + +-The starting point of the decision tree. For a decision tree, the classification or return target of all nodes is defined at the root node. If the target variable of the decision tree is discrete (ordinal or column-type variable), it is called a classification tree (classification tree), and if the target variable is contiguous (interval variant), it is called a regression tree (Regression). Branch Node + + + determines which branch the data enters, each branch node has a branch function---leaf node: Output of decision tree + output of leaf node + + + + Decision tree @@ -1381,6 +1391,9 @@ -1381,6 cluster query with km EANs training, the use of ' k:centroids can be light--Information gain formula + + + with entropy formula, the calculation of information gain formula is as follows:
Git diff odt file