ΑiSrSSKrSSKrSSKrSSKrSSKrSSKJ r /r Sr Sr /SQr SqSqSrSrS rSS jr\ "S S S SS9S5r\ "S S S SS9S5rSr\ "S S S SS9S5r\ "S S S SS9S5rg)z UCI Housing dataset. This module will download dataset from https://archive.ics.uci.edu/ml/machine-learning-databases/housing/ and parse training set and test set into paddle reader creators. N) deprecatedz:http://paddlemodels.bj.bcebos.com/uci_housing/housing.data d4accdce7a25600298819f8e28e8d593) CRIMZNINDUSCHASNOXRMAGEDISRADTAXPTRATIOBLSTATzYhttps://github.com/PaddlePaddle/book/raw/develop/01.fit_a_line/fluid/fit_a_line.fluid.tar 6e6dd637ccd5993961f68bfbde46090bcRSSKnURS5 SSKJn UR 5upE[ U5nUR [[U55X- SSS9 URS5 UR[[U55[5 URSU/5 URS5 URS 5 [R R#S 5(d[R$"S 5 UR'S S S 9 UR)U5 g)NrAggrcenter)coloralignz feature scale z./imagezimage/ranges.png0)dpi) matplotlibusematplotlib.pyplotpyplotsubplotslenbarlistrange set_titlexticks feature_namesxlim set_figheight set_figwidthospathexistsmakedirssavefigclose)maximumsminimumsrpltfigax feature_nums Z/var/www/html/banglarbhumi/venv/lib/python3.13/site-packages/paddle/dataset/uci_housing.py feature_ranger::sNN5#llnGCh-KFF U;  ("5S LL!JJtE+&'7HHb+ aR 77>>) $ $ IKK"K+IIcNc[b[bg[R"USS9nUR UR SU-U5nUR SS9URSS9URSS9UR S- pen[US- 5H"nUSS2U4Xg- XGXW- - USS2U4'M$ [UR SU-5nUSUqX8Sqg)N )sepr)axis) UCI_TRAIN_DATA UCI_TEST_DATAnpfromfilereshapeshapemaxminsumr&int) filenamer8ratiodatar3r4avgsioffsets r9 load_datarQPs!m&? ;;xS )D << 1 4k BD a a a4::a=(H;? #1a4j47*x{X[/HIQT $ A& 'F'6]NMMr;z2.0.0zpaddle.text.datasets.UCIHousingr@z>Please use new dataset API which supports paddle.io.DataLoader)since update_tolevelreasonc[[RRR [ S[ 55 SnU$)z UCI_HOUSING training set creator. It returns a reader creator, each sample in the reader is features after normalization and price number. :return: Training reader creator :rtype: callable uci_housingc3># [HnUSSUSS4v M g7fNr)rAds r9readertrain..readerxs%ACR&!BC&.  rQpaddledatasetcommondownloadURLMD5r\s r9trainrge1"fnn##,,S-EF! Mr;c[[RRR [ S[ 55 SnU$)z UCI_HOUSING test set creator. It returns a reader creator, each sample in the reader is features after normalization and price number. :return: Test reader creator :rtype: callable rWc3># [HnUSSUSS4v M g7frY)rBrZs r9r\test..readers%ACR&!BC&. r^r_rfs r9testrlrhr;c[RRR[S[ S5n[ R"USS9n[R"5nURUS9 U$)NrWzfit_a_line.fluid.tarr)mode)r.) r`rarbrcFLUID_URL_MODELFLUID_MD5_MODELtarfileTarFiletempfilemkdtemp extractall) parameter_tartardirpaths r9 fluid_modelrysYNN))229OM //-c 2C GNNN Nr;c[[RRR [ S[ 55 [SSS4$)zX It returns just one tuple data to do inference. :return: one tuple data :rtype: tuple rWrNr)rQr`rarbrcrdrerBr;r9predict_readerr|s:fnn##,,S-EF ! Sb ! ##r;cj[RRR[S[ 5 g)NrW)r`rarbrcrdrer{r;r9fetchr~s  NN""3 s;r;)g?)__doc__r-rqrsnumpyrCpaddle.dataset.commonr` paddle.utilsr__all__rdrer)rArBrorpr:rQrgrlryr|r~r{r;r9rs # B(  m4,"* / K    ( / K    (  / K  $  $ / K  <