From c3aa36cc7b9c42651c7681ec4518049f72c1b715 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D0=90=D1=80=D0=B7=D0=B0=D0=BC=D0=B0=D1=81=D0=BA=D0=B8?= =?UTF-8?q?=D0=BD=D0=B0=20=D0=9C=D0=B8=D0=BB=D0=B0=D0=BD=D0=B0?= Date: Thu, 16 Nov 2023 13:54:53 +0400 Subject: [PATCH] arzamaskina_milana_lab_1 is ready --- arzamaskina_milana_lab_1/README.md | 52 +++++++++++++ arzamaskina_milana_lab_1/img_screen_1.png | Bin 0 -> 339943 bytes arzamaskina_milana_lab_1/img_screen_2.png | Bin 0 -> 65641 bytes arzamaskina_milana_lab_1/main.py | 87 ++++++++++++++++++++++ 4 files changed, 139 insertions(+) create mode 100644 arzamaskina_milana_lab_1/README.md create mode 100644 arzamaskina_milana_lab_1/img_screen_1.png create mode 100644 arzamaskina_milana_lab_1/img_screen_2.png create mode 100644 arzamaskina_milana_lab_1/main.py diff --git a/arzamaskina_milana_lab_1/README.md b/arzamaskina_milana_lab_1/README.md new file mode 100644 index 0000000..66a2e25 --- /dev/null +++ b/arzamaskina_milana_lab_1/README.md @@ -0,0 +1,52 @@ +## Задание +Работа с типовыми наборами данных и различными моделями. +Сгенерируйте определенный тип данных и сравните на нем 3 модели + +Вариант №2 + +Данные: make_circles(noise=0.2, factor=0.5, random_state=1) + +Модели: ++ Линейная регрессия ++ Полиномиальная регрессия (degree=3) ++ Гребневая рекрессия (degree=3, alpha=1.0) + +## Используемые технологии +В лабораторной были использованы библиотеки: ++ matplotlib - используется для создания графиков ++ sklearn - используется для работы с моделями машинного обучения + +## Как запустить +Запустить файл main.py, который выполнит необходимые действия над моделями +и выведет графики на экран. + +## Что делает программа +Генерирует набор данных типа circles, делит его на обучающую и тестовую выборки. +По очереди обучает на данных обучающей выборки 3 модели: +модель линейной регрессии, модель полиномиальной регрессии со степенью 3 и +модель гребневой регрессии со степенью 3 и alpha=1.0. + +После обучения предсказания моделей проверяются на тестовых данных. +Строится 4 графика, один для отображения первоначальных тестовых и обучающих данных, где: +`o` - точки обучающей выборки первого и второго типа. +`x` - точки тестовой выборки первого и второго типа. +И по одному графику для каждой модели, где: +`o` - точки тестовой выборки первого и второго типа. + +Далее программа выведет оценки точности моделей. Полученные оценки: ++ Линейная регрессия - 0.268 ++ Полиномиальная регрессия со степенью 3 - 0.134 ++ Гребневая регрессия со степенью 3, alpha=1.0 - 0.131 + +## Скриншоты работы программы +График для отображения первоначальных тестовых и обучающих данных и +полученные графики разбиения точек на классы: + +Линейная регрессия - Полиномиальная регрессия (со степенью 3) - Гребневая регрессия (со степенью 3, alpha=1.0) +![img.png](img_screen_1.png) + +Вывод анализа точности работы моделей: +![img.png](img_screen_2.png) + +## Вывод +Исходя из этого, можно сделать вывод: лучший результат показала модель линейной регрессии. \ No newline at end of file diff --git a/arzamaskina_milana_lab_1/img_screen_1.png b/arzamaskina_milana_lab_1/img_screen_1.png new file mode 100644 index 0000000000000000000000000000000000000000..71980bb739364ab5d77101359d4166baab9380e9 GIT binary patch literal 339943 zcmeFZWl&sO7X?TX+`Z8dJh*#+&;$z*fT4hwbxpEH{U*glEOeGL4|{Z!;q2wpacg84}pVwb%^{Dc;$=s z*ccp~ADqkwF%>u6gLI@u!p_?V5WX08S(YIJTEbh#w_V|eVnulxCO zB&57$I6U7F6dA%X@cqMdUgSuB_t@9k_B9<^3|(#dyG-+e_0&r=(ZuyCxgIt&Fq@n% zuRT;3Q0P*!P#4)xphFm1vU3)UdYmv=FZZW!bE{4}o(VsluWR-tbY>9tuvcKWqF|Sc zNVKg(xm_V5*8#cg?xZTV`>g2{FQA^@UAGb@&w9VvWJU)2!QzCXOJwhpg+b;hqS|?~ zJ>He%l|=bM1Vj3_f_PazO4K(AWF7{zQ6x4I?qi7jIb{$w7#aA{AJ-9)6fn&?soVN~ z75}Yy<6j2TMz{PvF-=t@=M9rjqlMMrScMrkVkmZa7Rjk33cj({P&e5AgF0Kyo16lB zm;8#sV>1iw*m^5zG3NQk7`-?10qAJFJU*cB*18mDMaHTB-so4!clcx_N>lwZ?aH7>k5dz1bGpJ$KQgTr&1v*JP4RKk!m*=!-oY#xe zl0QHjXZt^Qm3=Ox1#EJ2-jI9((OOd7(s6dD)Y9#7JTqpEW4k*o(dN}twR5jkF=1>n zb_lkDdMKjcKOkJ1KzbX3%6UNW8cA@(##*gdDT>h1@Crt`Ui9cRTw;0e3)6i0L7ymG zv|sjFIfcZ+vT@}j3E7@#Iu@~Rc>kOznAsOX;;+&ZBHE(0`Si1Wi%>_ix?lAMG=KJp zQFWq@K90{+$T_QmWWq_N6(Koep`u81bH?`fw!I96wbSXOI4L^YU3lwBA#{$=f?X0s zCXR2wMqtD(XF}?o^ChC0YE})8L4ld9f@?g*jxZN4_}}w2y#1bS8B|NcL$Kt479pvo zZnl+Z#?;i-t6Fb(IjtAze(@cN!uw+M@s+OI+P9YITc?*^#++j0x7ES{W{(Qa_)CfB z5n>_jZ{qGbX?RTCTXG05JPE-VJZ8+!`O#;*Jgl#?x#S=;qbNszDp=gIZAHh&*ghw7 z%#-Me5ld2f(!J)}LXo}*$zD2JRdbN`pJ8mls*vzs+_X~(yB<%#u3%3o#2VHw`ihf01g zyz3@@le2=t#olS0&V52udh5V|xN}wtQ3>7+;K9xLd~_DiBd#yN=V{tGkV%N{aq(DF z!f$s!*${m+`>4<`;dsliI=)cJR6sAT8O%4a5cExSAVrvK+c^aUu8UL`La?fw)Qwba z6Y1f8@;*FBEBKYDdkeN%BD>eiV7vRQJrboWcsH@3!>W~c@sVj?lpnidxBIBVJ&apj z2WN_d0g*%F{8Ng8{hz+!zXM3O2^j4mGk5ru@OcuV6Kb0d=Q^$QUqyaxN$a)Jn`T)# zib(eI{(~3gV55&AYcG_xm#5I5tYgdO>LaLfd1*~gH0DpIX%e~kggx!)5HFCKzZAFC}L)rC3q($o~)whK}P zTh6-TJ_{{1IF_P&H1G74D=Qv}9wiK_xT}}KZ8r?OyKniqQV^~S4L(M86Z*;ke1=90 zDyC_|sj3Sz34i2T;9)C9XhkAW*I^!pF+`(JW%^n5Z$04taL>Fs0RTPzGSKBQ!cMoP z^{-{6VKbxG#v8r{4H2~4v_Kj+F(N7y|Ln727;2}sV{KX0zi6dl-(y-?o@Xc4$YQ97 z#2&1SzJ?)~tJ~xu1DViz`3|8{1A%4P{{zi#JC>+ZK3LK)mOVSxtUHqU)vH9zz6Z~n zcp5Y^rL!m15Yb`3M+JBSzU4Xwn=2`AEUVK+_f&6hb5C_199CcN;%;^2qq-G{jYKBD z&u8l+z1REeoiPfLSeU5&Ez)WaFs%l~=^?QasVmZSWB9XSPUG%7{0iVtNC+nx&y zZ;1`c{N(5}WWb@9H?;NO@HqPmwq2`mHru;t@;NHAu8(aYGGVNx``QX=%UO_I>0acrt!Fy~+i`U7EP?G_cRrUO+=YAZ-wjHqIMpbq+3- zgx;8B7G$w5Gv35m|{rzFn6;u zf`qzfS9ZqihkUgJ=qIcUV*AYaL29mK!Zz(hZ3$06>-JK>HxN0qwUuf29z zuAe#*ciLW3`jq_EQ^iGP+D?4WV5|e>L?0$#WZD9?vu8eeX-haKNhkM*D)P5vNK5B4 z{ir+Bd|V4LQLGREO*IYVD5gR#UN=#NDweR{1+KEF%Q7~5+x9z?ik>XYbERpm$o^cB zT0~WaSpQR2)_e(~&pXEQj{d&j{#{Xldzah6ftafgSBcwwb25!&0(*oVi)VY^?dCeQ zVq!|gytb~SwGM{(2GZ;#fO$cZ_4g$d`1?;6akqxEg=~+zsRj*$k7a{D_~u$%&IRM1 zrVg9BqZ?Ksfv^RSQK5ESKhu7bLN3iG2aVVDqpD!Kht2P~X9j;UI@R7%4Vbg?6oF#jz$NLD_Yc0D&pWep{)blJ_PB+l+bYa(p5zhgy{6N+}SrH$zJAz-0cO;qVKe zujhrED06})J1q6ovdTi#z^2QjS@hP=`fA7RZ&^(9)yqN+x0_X|d7BpM3#Oor&|~k$ zFLBj$gZHz(9Dj#>E&}bvSWUHkGE!l;P!>{gsQh~FJnG~So2GdjjrUivun>FR|LTw- zn6iT<@wDvFkm2&FQ2ZgpIuH>ffy&kn7131N<4!%4){5HvvrQBU57^!3{h+lof^wB0uLVDrA^MTy3h!xPh^z*-uc=)0qQPnX)qu|bMGPm5{sIoG`l7_U}U z2G^!kjebeL>Cf|U-F^2<<%HpPOQkK-eyTn_L%vP*{DYe!b%(#iAt9DDg;psOdZh+& z&b}#+T#ecex3}uL&drWog?&C2ix#2ZseMm~8Pw|UvD9^)l)Bf4Q-dc|<&Mi{=fov_ zjwUTP)7+Q6ry4I^mLIi`80pg*pQ015o2O+Pz`=zX4ZDA=m!EF>Pp-6+`&G#8dlX~P zy)2_M5j6qG^V&PBi_8RT9&ULxi}$Nico^(NzEMTHwE(Gn!9a6P`A=lDyoOlIQZ~+S zsSjLJv<)FVK!)qhGQ5Te`dUb@`>Kv%Lf4-t`7UP7O5WAaFNr?9b6z23YdJq{kfN9~ zA96L)F^%p|sPodCQdJK*{wjKRvcB6rT;|_CT;gyczfIxP$>N(qyri-2@HA_<`m6uR zO)E2lRrGW_KeM!@cW7DRN|{LqQ|YA8jH1pU#%MS>WFmfWr|dL^A{y4bps<(*8{ej$ zp0R?Vh^p5X$e5AWTQ27!d77)IiQ3#OL$Wm?MXGEvYFe~nl#{Z1qGxSonP(!B8~v)o zQYB!4P3_I=`5KMeEYN*}b$l}%+M|%IL3d^`%lyA}9Q%ofTjnfrMHFu3zVK@u`)K(V zY<6AbVZm3gn18yicgXvA0SilXfpn~7Zu8TT^IiJzGOziVXJW?KZMn&pNbX3bJR;bfy@@>&G;2sD|%|&~Gn}jjc~4=ROg<h~Q4#)UolIQVkjg8Ea=H<=X{Yx#<-5$v-*4F4b=P zD{Y6+e_MxffF~$kO2Zr`wHvnVTd|tbM}Z}@{5^zK zyh$`v9|~{l1mR#v)szWZ$skY-uU~Q?2)K z<5EA=oy%n|Z#U0gFN9X6PlQ~A#=L5E;ue9=_nug1?s4nigDPcgct>! 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