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training in separate folder

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gedin 2023-05-24 14:31:07 +02:00
parent c943af65cb
commit 296afadbe4
7 changed files with 76 additions and 25 deletions
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3
JenkinsfileTrain
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@ -1,7 +1,6 @@
node {
checkout scm
def dockerimage = docker.build("train-image", "dockerfile_train
")
def dockerimage = docker.build("train-image", "./train-eval")
dockerimage.inside {
stage('Preparation') {
properties([

23
dockerfile_titanic
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@ -1,23 +0,0 @@
FROM ubuntu:latest
RUN apt-get update --fix-missing
RUN apt install python3-pip -y
RUN apt install unzip -y
RUN apt install git -y
RUN pip install --user kaggle
RUN pip install --user pandas
RUN ln -s ~/.local/bin/kaggle /usr/bin/kaggle
ENV PATH="$PATH:~/.local/bin/kaggle"
ENV KAGGLE_USERNAME="wiktorbombola"
ENV KAGGLE_KEY=""
# RUN echo "alias kaggle='~/.local/bin/kaggle'" >> ~/.bashrc
COPY ./script.sh ./
COPY ./learning.py ./
# CMD ./script.sh 300
# CMD ./learning.py

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dockerfile_train → train-eval/Dockerfile
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0
eval.py → train-eval/eval.py
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0
learning.py → train-eval/learning.py
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train-eval/prediction.tsv Normal file
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train-eval/testing_data.csv Normal file
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@ -0,0 +1,38 @@
,Pclass,Sex,Age,SibSp,Fare,Survived
62,1,1,0.5574102175012645,1,0.16293234896625058,0
539,1,0,0.2665655032878098,0,0.09661756542473081,1
889,1,1,0.3171471927162367,0,0.05855610025741261,1
174,1,1,0.6965098634294385,0,0.05991421140938287,0
195,1,0,0.7218007081436519,0,0.2859895551532101,1
742,1,0,0.25392008093070306,2,0.5121218935012878,1
647,1,1,0.6965098634294385,0,0.06929138530460492,1
257,1,0,0.3677288821446636,0,0.16883675574220638,1
781,1,0,0.20333839150227617,1,0.11125659048908397,1
789,1,1,0.5700556398583713,0,0.15458810467956932,0
835,1,0,0.4815376833586242,1,0.16231419173453318,1
452,1,1,0.3677288821446636,0,0.05416439273810667,0
1,1,0,0.46889226100151743,1,0.13913573538264068,1
245,1,1,0.5447647951441578,2,0.17566830077223786,0
148,2,1,0.44992412746585736,0,0.050748620223090936,0
679,1,1,0.443601416287304,0,1.0,1
310,1,0,0.29185634800202326,0,0.16231419173453318,1
209,1,1,0.4941831057157309,0,0.060507970265993034,1
10,3,0,0.03894790085988872,1,0.03259622914329302,1
345,2,0,0.29185634800202326,0,0.025374310111545468,1
712,1,1,0.5953464845725848,1,0.10149724044618187,1
701,1,1,0.43095599393019723,0,0.05130978285055781,1
823,3,0,0.32979261507334345,0,0.024349578357040744,1
571,1,0,0.6585735963581184,2,0.10048070654571319,1
88,1,0,0.2792109256449165,3,0.5133418122566505,1
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627,1,0,0.25392008093070306,0,0.15216446768991498,1
737,1,1,0.43095599393019723,0,1.0,1
583,1,1,0.443601416287304,0,0.07831878409428937,0
796,1,0,0.6079919069296914,0,0.050610427826483444,1
262,1,1,0.6459281740010117,1,0.1554664461834305,0
748,1,1,0.22862923621648962,1,0.10364429745562033,0
809,1,0,0.4056651492159838,1,0.10364429745562033,1
486,1,0,0.43095599393019723,1,0.17566830077223786,1
730,1,0,0.3550834597875569,0,0.41250332793836464,1
177,1,0,0.6206373292867982,0,0.05604306762136532,0
520,1,0,0.3677288821446636,0,0.18249984580226933,1
1 Pclass Sex Age SibSp Fare Survived
2 62 1 1 0.5574102175012645 1 0.16293234896625058 0
3 539 1 0 0.2665655032878098 0 0.09661756542473081 1
4 889 1 1 0.3171471927162367 0 0.05855610025741261 1
5 174 1 1 0.6965098634294385 0 0.05991421140938287 0
6 195 1 0 0.7218007081436519 0 0.2859895551532101 1
7 742 1 0 0.25392008093070306 2 0.5121218935012878 1
8 647 1 1 0.6965098634294385 0 0.06929138530460492 1
9 257 1 0 0.3677288821446636 0 0.16883675574220638 1
10 781 1 0 0.20333839150227617 1 0.11125659048908397 1
11 789 1 1 0.5700556398583713 0 0.15458810467956932 0
12 835 1 0 0.4815376833586242 1 0.16231419173453318 1
13 452 1 1 0.3677288821446636 0 0.05416439273810667 0
14 1 1 0 0.46889226100151743 1 0.13913573538264068 1
15 245 1 1 0.5447647951441578 2 0.17566830077223786 0
16 148 2 1 0.44992412746585736 0 0.050748620223090936 0
17 679 1 1 0.443601416287304 0 1.0 1
18 310 1 0 0.29185634800202326 0 0.16231419173453318 1
19 209 1 1 0.4941831057157309 0 0.060507970265993034 1
20 10 3 0 0.03894790085988872 1 0.03259622914329302 1
21 345 2 0 0.29185634800202326 0 0.025374310111545468 1
22 712 1 1 0.5953464845725848 1 0.10149724044618187 1
23 701 1 1 0.43095599393019723 0 0.05130978285055781 1
24 823 3 0 0.32979261507334345 0 0.024349578357040744 1
25 571 1 0 0.6585735963581184 2 0.10048070654571319 1
26 88 1 0 0.2792109256449165 3 0.5133418122566505 1
27 366 1 0 0.7470915528578654 1 0.14687821814567664 1
28 627 1 0 0.25392008093070306 0 0.15216446768991498 1
29 737 1 1 0.43095599393019723 0 1.0 1
30 583 1 1 0.443601416287304 0 0.07831878409428937 0
31 796 1 0 0.6079919069296914 0 0.050610427826483444 1
32 262 1 1 0.6459281740010117 1 0.1554664461834305 0
33 748 1 1 0.22862923621648962 1 0.10364429745562033 0
34 809 1 0 0.4056651492159838 1 0.10364429745562033 1
35 486 1 0 0.43095599393019723 1 0.17566830077223786 1
36 730 1 0 0.3550834597875569 0 0.41250332793836464 1
37 177 1 0 0.6206373292867982 0 0.05604306762136532 0
38 520 1 0 0.3677288821446636 0 0.18249984580226933 1