From 2d3ac04476f941f830763b437a2b7bcea3be5939 Mon Sep 17 00:00:00 2001 From: dhananjay93 Date: Tue, 30 Oct 2018 05:22:41 +0000 Subject: [PATCH 1/6] Done --- __pycache__/__init__.cpython-36.pyc | Bin 164 -> 154 bytes .../__pycache__/__init__.cpython-36.pyc | Bin 178 -> 168 bytes .../__pycache__/build.cpython-36.pyc | Bin 650 -> 645 bytes q01_load_data/build.py | 14 ++++++++++++-- .../tests/__pycache__/__init__.cpython-36.pyc | Bin 184 -> 174 bytes .../test_q01_load_data.cpython-36.pyc | Bin 3979 -> 3969 bytes 6 files changed, 12 insertions(+), 2 deletions(-) diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc index ebbd53a2d5f8e74c1825d49e211ea6c89bbb6b24..2cc169ef5b6eb158a6ec0860767c7975baf4a825 100644 GIT binary patch delta 53 zcmZ3&IE#_Pn3tE!dvT+*JLM~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXRq0+*JLM~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXWlCd`WT<7SVNL7fEH$h(Of`%t z%o9H;X-9DeC+4IE6lEr-YBJs8DN4*s$g>Qh$)kw86?OCBsds(m{^zr#RfYx delta 206 zcmZo=?PBFL=H=yL378jkcp~R=#)ydK&a6tk#Z#1+my(|wUtE${lKS#L5EOARFfdFu zWmMs012T%(LA-266YUuNjQreG{luhiaXZ3Vc28jHDr1Op=%qZp&mWL~CBekPD0$XpIa9%dF+07eiu<^TWy diff --git a/q01_load_data/build.py b/q01_load_data/build.py index e4cd8e3..f3d8679 100644 --- a/q01_load_data/build.py +++ b/q01_load_data/build.py @@ -1,10 +1,20 @@ +# %load q01_load_data/build.py # Default imports import pandas as pd from sklearn.model_selection import train_test_split - path = 'data/house_prices_multivariate.csv' - # Write your solution here +def load_data(path,test_size = 0.33,Random_state= 9): + df = pd.read_csv(path) + X = df.iloc[:,:-1] + y = df['SalePrice'] + X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = Random_state, test_size= test_size) + return df, X_train,X_test,y_train,y_test + + + + + diff --git a/q01_load_data/tests/__pycache__/__init__.cpython-36.pyc b/q01_load_data/tests/__pycache__/__init__.cpython-36.pyc index 133357e0803cc77a9fa179800aad36162ab7db97..414cc95de5f8ddcdd2a566081ccb9683e60dbc85 100644 GIT binary patch delta 53 zcmdnNxQ>y-n3tE!{MGg7i5%vN(fS$rxvBao8Hss`d0B~-md5(w`9;~q1&PV2`pNkz IsS~sO0M%v^c>n+a delta 63 zcmZ3-xPy_yn3tD})qh^pL=JQ9RQ-(n+*JLM~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAX)_{M=Oil#Il@#JsG;N=sw?@cg3e;)2BFRQ=@q Kl+;a3-Mjz?(%jU%l4AYzqSVU7lKfo# V#GD+3f};Ga)Z~)l&EFWic>(+j7*YTL From 83ae9e09d5dbc2aa660d073284f6309b194c1ec8 Mon Sep 17 00:00:00 2001 From: dhananjay93 Date: Tue, 6 Nov 2018 11:22:41 +0000 Subject: [PATCH 2/6] Done --- .../__pycache__/__init__.cpython-36.pyc | Bin 190 -> 180 bytes .../__pycache__/build.cpython-36.pyc | Bin 636 -> 924 bytes q02_Max_important_feature/build.py | 15 +++++++++++++-- .../tests/__pycache__/__init__.cpython-36.pyc | Bin 196 -> 186 bytes ...st_q02max_important_feature.cpython-36.pyc | Bin 1735 -> 1725 bytes 5 files changed, 13 insertions(+), 2 deletions(-) diff --git a/q02_Max_important_feature/__pycache__/__init__.cpython-36.pyc b/q02_Max_important_feature/__pycache__/__init__.cpython-36.pyc index 93c9119e93bd10425c9a680002a7f8007ca6fad4..2231f57fb23da7f98203c93c409d881b2a27c857 100644 GIT binary patch delta 53 zcmdnTxP_6!n3tE!M~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAX-i_^znkqS^ z969h9JPGgM8{*Vg=!tPqp@-ttjAzE4*>Aq_{?=CaarX1W4}#DybZtdozW}iVP#kfr zP>C~)gH064S_1Rd3V)0;nnhWhC0Se0tix&6WFJi=z>ln9xn)w@1ZYb7p?FLFC(7t_BmQaufWH! z2f&90L)F*5Gi_vXVk_f3Rm{3H@|2xQ>pRRALUXCdK9RastPq}_NX`9*W_ev%>13rZ zLX{$@uz+9`Iv9f3+n~mP`%`;~7x){Q(joee%oc=G;z@7MW4ZR$>hd!%Rf;}8W}4{< zn?Kv{zpKoNt>MT0qT-^@_>Ad7@LWkPn8}S88(}S==uh{a=5N?(F3TD^VcO+Kg1N?s z{-}|P_v-m&cc7$oMOD@Z+W}s{8l$uH#eu?Q(J_>mGGYmb@7Bae%J446Qe-?-+etV5b0B2STvaML>iwUt-gNIt{`aBw))bk*hmUkq)^oEH zYTgflS5Z<4pO>L{7sPyJVFd#(m(t{R7@n#jgEkazgYnzatve{~dh)DJ5q2wyw zeFNXXcgWRKUqL)Lsh1ASH~-(vyj6dV^WA21!906spBSNUG$$tb2cYRTfItF=D8dY5 zB(Wf4d}%VmC^MMJD#8+`s61m<71hbr+T?Ek(SV^+k4lCufD8p_j56Fp4>Y3z7Qpg~ z1*$5FP(T8Dfo!9DV&kI5Q%}aik9$)%46=pcB}x_bG*Q~U<>64Kh3Usaj*7~E z2tAhIn!BmgnB`AorOhY|eIV5Yil4sIPa^5?>%Q+CC*ClUu}+N}+jMhh bR-dh(gGFd7ti31^!%%hzL^HkyT{ivzktboO diff --git a/q02_Max_important_feature/build.py b/q02_Max_important_feature/build.py index 51fbde6..2da3d4f 100644 --- a/q02_Max_important_feature/build.py +++ b/q02_Max_important_feature/build.py @@ -1,8 +1,19 @@ +# %load q02_Max_important_feature/build.py # Default imports from greyatomlib.advanced_linear_regression.q01_load_data.build import load_data - +import numpy as np # We have already loaded the data for you data_set, X_train, X_test, y_train, y_test = load_data('data/house_prices_multivariate.csv') +df = data_set +target_variable = 'SalePrice' +# Write your code here +def Max_important_feature(data_set,target_variable = 'SalePrice' , n=4): + a = data_set.corr()[target_variable] + b = a.sort_values(axis=0, ascending=False, inplace=False, kind='quicksort', na_position='last') + c = list(np.array(b.index[1:n+1])) + return c + + + -# Write your code here diff --git a/q02_Max_important_feature/tests/__pycache__/__init__.cpython-36.pyc b/q02_Max_important_feature/tests/__pycache__/__init__.cpython-36.pyc index cec58d46190aacd7d84dfc496a3158043f55733c..375319204981da5f9a0e6c75678a2620dd7145e9 100644 GIT binary patch delta 53 zcmX@YxQmg)n3tE!G~P@xvBao8Hss`d0B~-md5(w`9;~q1&PV2`pNkz IsS~rJ0NZ{NrT_o{ delta 63 zcmdnRc!ZI|n3tD})qh^pL=JQ9Lj8>V+*JLM~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAX4n3tE!Ib}@^e%5Q!*0s67#YWD=m%n!}E)>iwhEyQ}vVc MQ&Km7WxT`!04|RduK)l5 delta 66 zcmdnXdz_cUn3tF9r~kaDjU0y Date: Sat, 8 Dec 2018 19:22:26 +0000 Subject: [PATCH 3/6] Done --- .../__pycache__/__init__.cpython-36.pyc | Bin 179 -> 169 bytes .../__pycache__/build.cpython-36.pyc | Bin 892 -> 906 bytes q03_polynomial/build.py | 15 ++++++++++++++- .../tests/__pycache__/__init__.cpython-36.pyc | Bin 185 -> 175 bytes .../test_q03_polynomial.cpython-36.pyc | Bin 1393 -> 1383 bytes q04_ridge/__pycache__/__init__.cpython-36.pyc | Bin 174 -> 164 bytes q04_ridge/__pycache__/build.cpython-36.pyc | Bin 975 -> 898 bytes q04_ridge/build.py | 14 +++++++++++++- .../tests/__pycache__/__init__.cpython-36.pyc | Bin 180 -> 170 bytes .../__pycache__/test_q04_ridge.cpython-36.pyc | Bin 2080 -> 2096 bytes 10 files changed, 27 insertions(+), 2 deletions(-) diff --git a/q03_polynomial/__pycache__/__init__.cpython-36.pyc b/q03_polynomial/__pycache__/__init__.cpython-36.pyc index aa42922819662c41fcd07685edf2a72bf7ac881e..3057c5e83c5f8f1440ae50d90831eeb71a37f4cd 100644 GIT binary patch delta 53 zcmdnYxRQ~>n3tE!QxvBao8Hss`d0B~-md5(w`9;~q1&PV2`pNkz IsS~q20n#B7VgLXD delta 63 zcmZ3M~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXL|>l5L$^JCh7I=om6jf``#x z;8E}w_3CMVK|J^}FY|@>k?$q>-uLoDUklX(&vPEO+`Gs?=nJic1^W|7Iha?^_PNa{ zE3hK7+vYY3Z0`Ky4l6O2c`rEd*m@n+%Jb1iL)KJ!pOsv!bW#j6+Msmt{TW}t@QQYhe8E@Q2p{!8> zL!iKGMXI4h7|Yf)5&gVyt63Ba?IkzhG%t+*N;R5WgXD>ez`YJ*mh>A^g^K6qAnA<* zs98;93LL|H;H(VgRsf{Cfvk+_D*)P z3$nYp4iBUQfQXA7OtFhaC3_~Hb^SX51(RGVv9=^&Pm>CeWv3M=LoF{JfsbL2AM1go PmUcl8ma&1$xNQ6aWI1w8 delta 461 zcmYjNJ4*vW5Z>K;)}vB)g*G2gfI*qx`suU_9X&2r=B&Hg3`eW4Z8AU+0)$S7p4Q|>Iry!03Z>=j4*|%J#`C>iNs??5~-w!X-t11 zQcdv$PsmtJ)q$3hRDoDaHJDMjn3eGE!+8_ih8Mbi!no7%Xx!AZLfesodSO-=Ed!y# zETQC(kI$5@Cm~N8M)zFUhM*yf0ww#$^D6 zYgomb*ubJXdnTWkMbK;=KEh)u@+I0jd?qJVAd8VJum)OIJcJh|K0nIWz36H{KRC*| F`Ug&5aW?<} diff --git a/q03_polynomial/build.py b/q03_polynomial/build.py index 26d8971..3291645 100644 --- a/q03_polynomial/build.py +++ b/q03_polynomial/build.py @@ -1,3 +1,4 @@ +# %load q03_polynomial/build.py # Default imports from greyatomlib.advanced_linear_regression.q01_load_data.build import load_data from sklearn.preprocessing import PolynomialFeatures @@ -6,6 +7,18 @@ # We have already loaded the data for you data_set, X_train, X_test, y_train, y_test = load_data('data/house_prices_multivariate.csv') - +X_train = X_train[['OverallQual','GrLivArea','GarageCars','GarageArea']] +X_test = X_test[['OverallQual','GrLivArea','GarageCars','GarageArea']] # Write your solution here +def polynomial(power=5,Random_state=9): + # PolynomialFeatures (prepreprocessing) + poly = PolynomialFeatures(degree=power,include_bias=False) + poly_x = poly.fit_transform(X_train) + regressor=LinearRegression() + model = regressor.fit(poly_x,y_train) + return model + + + + diff --git a/q03_polynomial/tests/__pycache__/__init__.cpython-36.pyc b/q03_polynomial/tests/__pycache__/__init__.cpython-36.pyc index 6e2087691199f0bc7e5f879b594cb46948bbd2d5..a1dc0bc4f3ef33424272ad7b91efd0e8e0b124a4 100644 GIT binary patch delta 53 zcmdnVxSo;2n3tE!M~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXY%7!}j?GxBp&^;0qu^Ahv25-Tl@^~3XvvWp86lT-DR Y^HWkcA7hkaV!fzz`={RKr_4Q!06a4pBLDyZ delta 78 zcmaFP^^uFyn3tC;Gh$wp-bT(zjM|0z8Tq-X`iV&ynffmI$)&lec_qdA=|!oPi6!~D i`iVI?3I#>^S*gh-#hdpqN-?p{nmKc(<>uSWJ&XVy-n3tD})qh^pL=JQ9X#I@*+*JLM~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAX1gh5Z<5L`?sA0niNPB2+0jsqyizLfFeYJ3)@oADU!AFZtNWP-Dz(l;c%x& zF)c{eJp~P~K*0kbQEmkl@CsDSIuy)kKFv3~v)}A|^{&0(pwkI|?Z>B&Ho@>tAlMq8 zvNTMiG)_BdSF)^^?Fe^`G1|O&y7_$X>UV$;`uXO zk-&lo`kpqp#u?T`(=};GO)^K5HE!rO1IfnGZcXi}aBiW70dutXkGVCg-5Q_K5$dyn zKUP+zPudT7Kbk=b_WiK$w_ou6EBDnz%StN>MdPlvr0*HV7v-EAwk(8Pq`^?ml&q>k zr7>Jl{5+qON{TePX}BTb@a5=uG9Dhi7(mB1KOT)gBGrSp{|u6Ov6P9J^PJ}yUp+iX zP6`#hu1Y?Y$rNyl;IL0A(7hLVO-$>Fkq!fnb7t3;GNM5#k z^yDn{1=oC1Nv-U@Rb(Nw5Ca%j@mv&3<5W@#wQK8ktpC7D8vil;_+lZS*nMmVh_MeI KhgEP5LWxawW=emVWEN-bval7z z!wSRPy?gNw@b1}rZ=S?|!ILjt6%*cM~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXBE&(2#N?0c!jnx|6~PAStAZTC3dCSX zC;=I$j;LYCVyt1D+{Gq6`3S2KF5|@5lv(%~s}v{4u}V%3V-o~B4UeglTi6VhrGb`d mG8KUwP$UCl<8bRUgyGVYHP|f#Btbf)K!hxakegh~wiZ|b8%x08jW?*1o17c?&E>;5)B@8Ky&5SWjwT!h)lT(=|i!c{) z1BGv~7UdSF8bT Date: Sat, 8 Dec 2018 19:27:55 +0000 Subject: [PATCH 4/6] Done --- q05_lasso/__pycache__/__init__.cpython-36.pyc | Bin 174 -> 164 bytes q05_lasso/__pycache__/build.cpython-36.pyc | Bin 975 -> 896 bytes q05_lasso/build.py | 14 +++++++++++++- .../tests/__pycache__/__init__.cpython-36.pyc | Bin 180 -> 170 bytes .../__pycache__/test_q05_lasso.cpython-36.pyc | Bin 2080 -> 2070 bytes 5 files changed, 13 insertions(+), 1 deletion(-) diff --git a/q05_lasso/__pycache__/__init__.cpython-36.pyc b/q05_lasso/__pycache__/__init__.cpython-36.pyc index 1005306dfd1495f17293e8f96d1fe442f494d410..46c4a00352226a1c86bb56ab7c45b718eeab9653 100644 GIT binary patch delta 53 zcmZ3-xP+0zn3tE!y-n3tD})qh^pL=JQ9X#I@*+*JLM~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXn7YE5nkc32ncyJH13y~(UG~1o5S`oV6u8$P}ppCs!by%z|& z!Y7o4EMhV1vYw<_Kid-C3S+dsI9z{uaQ!<#2>rUc{rUON%lG?J49uDjK_Q+&R4IT) zH4<15;e2o!T;mLDqMa3KNKGr^3C38VbzS{y*l`wDwNP2o30P ztUN0+AniwdCpv=^?8p9~(|*Mduf10jEi0`YC>n3MAp_q~J}+n7&_yBSoCT>oQ?jZG z#bUUk`0IR9Dk)fW({Mw=^yTPiGENU(454F_AC1PJkm|$Re}>7dSja@oc+T^TFQ4ot z$AyaCR3)FvWC}X%JM!qhp>qyGThLPV01)os7>D3JaJAijCrRIsQW%<_FUqAMdD-qb z$EU0#xaN~eYGt>rA`78~7{GXn=b~5`w~|t*ZCkfv{RdXkbe_VG&*yT_?qf4Rj62{l Kj-4G6yMF;pP=0*? delta 612 zcmYjNL5tKd6mHU{ozAr5?4TY5K}3XJEb76_qM(aj#Dfa1K`61w?o4Ugnq(Gd?Xp4@ zPb&;__vFQkKftR$zo4 zL{SHT!$RtJ;2FXZj`0|u!jsj@+vsQLIL_+JrQ;v3PJh1l{qW7L92mwf-vlyo$AmmE zpq$pBfI{k?xJRG`1yE4A9R!ZaJq0^(1Qja$7E*5?P;>&#Jtzh$RBj79`|kG2p~<{n z>HSp_Lu{m@*6XFHbz8ItA32Ht;IXicB(6rJY-U7gBTnN&nE9N#BW z)>$JMo#!e6I>_sC!7G_W>v!PtF>ELfcZec)1>sD?s?nZ&A(U{9zxH=C#iY{yvOg1F z1eQjnHO28C*GvgAuQU=|va2}y$J)xCy!OcvXH4O*-E>xSmXhbQdAd{Q3x1AON~ZgQ zEs3gmO3Ly=BkF?XO0I9fD;LGol#NYDn>b($A}|CKFo7Es)Ad`JZi(1DYE&(FvlLdo z{tBP$X@Bz-W+KKY9#Au8CYcf=qYx7dk%cV_*1vD^KR9bRJ=o?oU6kx5G&gC@BQP*K JvfG_{zX66Jpcw!F diff --git a/q05_lasso/build.py b/q05_lasso/build.py index fb30d50..937b2f4 100644 --- a/q05_lasso/build.py +++ b/q05_lasso/build.py @@ -1,14 +1,26 @@ +# %load q05_lasso/build.py # Default imports from sklearn.linear_model import Lasso import pandas as pd import numpy as np from sklearn.metrics import mean_squared_error from greyatomlib.advanced_linear_regression.q01_load_data.build import load_data -np.random.seed(9) # We have already loaded the data for you data_set, X_train, X_test, y_train, y_test = load_data('data/house_prices_multivariate.csv') +np.random.seed(9) + # Write your solution here +def lasso(alpha = 0.01): + model = Lasso(alpha, normalize= True,random_state=9) + Regressor = model.fit(X_train, y_train) + y_train_pred = Regressor.predict(X_train) + y_test_pred = Regressor.predict(X_test) + RMSE_TRAIN = (mean_squared_error(y_train_pred, y_train))**0.5 + RMSE_TEST = (mean_squared_error(y_test_pred, y_test))**0.5 + return RMSE_TRAIN,RMSE_TEST + + diff --git a/q05_lasso/tests/__pycache__/__init__.cpython-36.pyc b/q05_lasso/tests/__pycache__/__init__.cpython-36.pyc index 88694349bfe01743507f538dd58873ee81a6ec3c..6ac6a13dfd8d3c5d4a7e226bc93039f90b42988a 100644 GIT binary patch delta 53 zcmdnOxQda(n3tE!M~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXiwhEyQ}vVc MQ&KlSWwd4k02X@_lK=n! delta 66 zcmbOxut0#rn3tF9r~kaDjU1a8wbS)8@^e%56O%GB^ Date: Sun, 9 Dec 2018 11:07:50 +0000 Subject: [PATCH 5/6] Done --- .../__pycache__/build.cpython-36.pyc | Bin 906 -> 837 bytes q03_polynomial/build.py | 12 +++++------- .../__pycache__/__init__.cpython-36.pyc | Bin 185 -> 175 bytes .../__pycache__/build.cpython-36.pyc | Bin 702 -> 761 bytes q06_cross_validation/build.py | 10 ++++++++-- .../tests/__pycache__/__init__.cpython-36.pyc | Bin 191 -> 181 bytes .../test_q06_cross_validation.cpython-36.pyc | Bin 2091 -> 2081 bytes 7 files changed, 13 insertions(+), 9 deletions(-) diff --git a/q03_polynomial/__pycache__/build.cpython-36.pyc b/q03_polynomial/__pycache__/build.cpython-36.pyc index dd8639b06dd6bbd53240037995e3905b5b5d126b..0f3f5b430d65b01a9e568936fbf992c9668e9902 100644 GIT binary patch delta 250 zcmeBTKgz~w%*)HQX9iD<^F~f*#(HK31_lsz2I67`AW_0l!dS!5%vi$I%+SnK%T&XZ z#azNt!rIKl$WX%+%%I8Wr^!~t0#sQ9(pSU^ByKUMWtQAxkBBcRO3ci=#a;iQN$#ufXo253LMZTBc$o_ii#jB+B%h=w9a&>b z2HaCi2h;~$unszE*+6>Mv0IeW>t#+Hm+A?W5=qrQ)-O^O4^?S$4%D9$>8i4Yg|am( z4UG%$CR4S*eCgdt6Z?r^;YnS#hZv=S~Et2V~v)o z{z5Pt|FAqhoPLNs5J_;1IZiOl$0hkWKk%90enuG!b8lewAK7?DPeXcyGn~;K^oC41 diff --git a/q03_polynomial/build.py b/q03_polynomial/build.py index 3291645..b381a59 100644 --- a/q03_polynomial/build.py +++ b/q03_polynomial/build.py @@ -5,6 +5,7 @@ from sklearn.pipeline import make_pipeline from sklearn.linear_model import LinearRegression + # We have already loaded the data for you data_set, X_train, X_test, y_train, y_test = load_data('data/house_prices_multivariate.csv') X_train = X_train[['OverallQual','GrLivArea','GarageCars','GarageArea']] @@ -13,12 +14,9 @@ # Write your solution here def polynomial(power=5,Random_state=9): # PolynomialFeatures (prepreprocessing) - poly = PolynomialFeatures(degree=power,include_bias=False) - poly_x = poly.fit_transform(X_train) - regressor=LinearRegression() - model = regressor.fit(poly_x,y_train) - return model - - + poly_model = make_pipeline(PolynomialFeatures(power), + LinearRegression()) + poly_model.fit(X_train,y_train) + return poly_model diff --git a/q06_cross_validation/__pycache__/__init__.cpython-36.pyc b/q06_cross_validation/__pycache__/__init__.cpython-36.pyc index fa7d8bff4b4367609876242346df0325d2410dff..45fbc25d5cb2937fb50f1e1086ecf2b15e1e0c79 100644 GIT binary patch delta 53 zcmdnVxSo;2n3tE!M~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAXY5QcYevv-$pi6Mj(f*?c=(s)H|1QmN5QSc)OamlXcF886kYY{lHh;51^ zwSPtMZ)|HN*jR~H&c!AJGxNSM`||87{h{4{ya6H?YaH=P zY$wjZDURFgf<*PG!R;Bwh&$YUMuRnOouXc~kbbp?4Lu3@ttei$=tmVYinosM!_HBJ zG}hM4!bp=GP?$}5Kql}Bi93OQ&I8`=s>JcI3oITbE$mr;W7l95 delta 380 zcmYk1u};G<5Qc3haYB@Is5*5*Dnja%N-!b>f{6)JsHufbq1P2=~=r^ydS=mTw30R9N1&ziv?7G6P% zko)(zIq!8i<>3RGq?}x!Vbt912A^9HZC-Xpxd+CT4+=piAl-*%&>9(R2*;do?=iUb z)?VSYUA({W6@h>a$5W%&qPF4c-}sea_0YFLCAlaq9$UPcP@PL9^fOWkOnv9sTvj4u zSMx=7D)VI}YNNB65-Vn8m9etizEQFeIlQ*Vq~E^bQ7?5=4iVulRvkEpoi--dGpbn4 zWo3OW1h)}qhE26FibBLv02JCNx0j^==`L>gk7T2{?`?Dd)XP#Fy5)2XEx{2^NJ6^7 EFRjd6h5!Hn diff --git a/q06_cross_validation/build.py b/q06_cross_validation/build.py index e39b93b..a127722 100644 --- a/q06_cross_validation/build.py +++ b/q06_cross_validation/build.py @@ -1,13 +1,19 @@ +# %load q06_cross_validation/build.py # Default imports from sklearn.model_selection import cross_val_score import numpy as np from greyatomlib.advanced_linear_regression.q01_load_data.build import load_data +from sklearn.linear_model import Ridge -np.random.seed(9) # We have already loaded the data for you data_set, X_train, X_test, y_train, y_test = load_data('data/house_prices_multivariate.csv') - +np.random.seed(9) # Write your solution here +def cross_validation(model, X,y): + model.fit(X_train,y_train) + scores = cross_val_score(model, X, y, scoring='neg_mean_squared_error', cv=5) + return scores.mean() + diff --git a/q06_cross_validation/tests/__pycache__/__init__.cpython-36.pyc b/q06_cross_validation/tests/__pycache__/__init__.cpython-36.pyc index ca3f5cd76d3a5d9abb66f9d0edaf0d9dac4ec0bc..c76ef5adfc40e631f20a545193a96ae83a678471 100644 GIT binary patch delta 53 zcmdnbxRsH^n3tE!M~`m;B_?+|<01V*T`@)XKz?{9OIS SoE(LMqWrAX Date: Sun, 9 Dec 2018 11:10:59 +0000 Subject: [PATCH 6/6] Done --- q03_polynomial/__pycache__/build.cpython-36.pyc | Bin 837 -> 884 bytes q03_polynomial/build.py | 4 +++- 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/q03_polynomial/__pycache__/build.cpython-36.pyc b/q03_polynomial/__pycache__/build.cpython-36.pyc index 0f3f5b430d65b01a9e568936fbf992c9668e9902..14d2f204ac6b8d4dbca9476ca914535926c57956 100644 GIT binary patch delta 268 zcmX@g_JvK^n3tE!@&`{$6*B|FV+JI^3S>I~adFK=6z&wh zUM5C{6#ifaO~HvXcDRBRJA)Lf0ErTY62=;a6vh;$UZxVJW`<^_TBaJNEanoH64qv* zwi+g&HfBFJO~xpm%)I2B(v;Nrq|C(P$qkH#a<_Pb67y2>bK{Fk5=&B}xC-)fD&uqW zQ&MwQG8FMnKF^ph!o$eH$irB~541{?sfZg$74b}VV>)IH5-H+ECHR2cTO2k(6H0SZ a?SP(SC>8(`JU|nGkVS}5fKh;%iyZ(wJU3qe delta 221 zcmeyuc9c!on3tDp&kUXzXJ!V5#|%h-707k~;^Kmd%4z)kDLg5>EsRmTDSW{UngSD- z>@WaoU~mR0PyiAo3?+;;49$!sOwA0?MsXG7=Tye$=BK3QtYj$Snf!qcz6krAb7(y)F diff --git a/q03_polynomial/build.py b/q03_polynomial/build.py index b381a59..b1d3371 100644 --- a/q03_polynomial/build.py +++ b/q03_polynomial/build.py @@ -14,9 +14,11 @@ # Write your solution here def polynomial(power=5,Random_state=9): # PolynomialFeatures (prepreprocessing) - poly_model = make_pipeline(PolynomialFeatures(power), + poly_model = make_pipeline(PolynomialFeatures(power,include_bias=False), LinearRegression()) poly_model.fit(X_train,y_train) return poly_model +polynomial(power=5,Random_state=9) +