{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Lineaarinen regressio: tehtävä" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Olet töissä ison yrityksen markkinointiosastolla myynnin tukena ja osastosi suunnittelee markkinointikampanjoita, jotka on tarkoitus ohjata eri kanavien kautta. Sinulla on tietoa myynnistä ja eri markkinointikampanjoista. Tehtäväsi on kehittää myynnin ennustamismalli. Mallin on tarkoitus toimia myynnin suunnittelu tukena ja antaa tietoa siitä, kuinka paljon myyntiä voidaan odottaa, jos markkinointiin käytettään tietty määrä rahaa kunkin kanavan kautta." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# tuodaan datankäsittelyyn vaadittava kirjasto\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# datan lataaminen vaatii nettiyhteyden\n", "df = pd.read_csv('http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv', index_col = 0)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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TVradionewspapersales
1230.137.869.222.1
244.539.345.110.4
317.245.969.39.3
4151.541.358.518.5
5180.810.858.412.9
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" ], "text/plain": [ " TV radio newspaper sales\n", "1 230.1 37.8 69.2 22.1\n", "2 44.5 39.3 45.1 10.4\n", "3 17.2 45.9 69.3 9.3\n", "4 151.5 41.3 58.5 18.5\n", "5 180.8 10.8 58.4 12.9" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tutkiskellaan dataa tulostamalla vaikka ensimmäiset tai viimeiset rivit datakehyksestä\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(200, 4)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# katsotaan datakehyksen muoto\n", "df.shape" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 200 entries, 1 to 200\n", "Data columns (total 4 columns):\n", "TV 200 non-null float64\n", "radio 200 non-null float64\n", "newspaper 200 non-null float64\n", "sales 200 non-null float64\n", "dtypes: float64(4)\n", "memory usage: 7.8 KB\n" ] } ], "source": [ "# tulostetaan vielä datakehyksen tiedot\n", "df.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ennen kuin alotat mallin kehittämisen, haluat saada käsityksen datasta. Valitset tätä varten sopivat kirjastot ja piirrät pari kuvaa. (Enemmänkin saa piirtää - tämä on jopa suositeltavaa.)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "\n", "sns.set()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# piirrä muuttujista parittaiset kuvat. pohdi jo tässä vaiheessä, mitä odotat mallilta\n", "sns.pairplot(df)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/anaconda3/lib/python3.6/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n", " return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# piirrä parikuvat muuttujista myyntiä vasten. lisää kuviin regressiosuora. \n", "# selventääkö tämä odotuksiasi mallin suhteen?\n", "sns.pairplot(df, x_vars = ['TV', 'radio', 'newspaper'], y_vars = 'sales', \n", " height = 5, aspect = 0.7, \n", " kind = 'reg')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Seuraavaksi varmistat, että selittävien muuttujien välillä ei ole liian suurta korrelaatiota." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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TVradionewspapersales
TV1.0000000.0548090.0566480.782224
radio0.0548091.0000000.3541040.576223
newspaper0.0566480.3541041.0000000.228299
sales0.7822240.5762230.2282991.000000
\n", "
" ], "text/plain": [ " TV radio newspaper sales\n", "TV 1.000000 0.054809 0.056648 0.782224\n", "radio 0.054809 1.000000 0.354104 0.576223\n", "newspaper 0.056648 0.354104 1.000000 0.228299\n", "sales 0.782224 0.576223 0.228299 1.000000" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# laske korrelaatiomatriisi\n", "corr = df.corr()\n", "corr" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# havainnollista vielä varmuuden vuoksi tilannetta lämpökartan avulla\n", "sns.heatmap(corr)\n", "\n", "plt.xticks(range(len(corr.columns)), corr.columns)\n", "plt.yticks(range(len(corr.columns)), corr.columns)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Datasi näyttää melko lupaavalta, joten siirryt valmistelemaan sitä oikeaan muotoon analyysia varten. Jaat ensin datan vektoriin, jossa on endogeeninen muuttuja sekä matriisiin, johon tulevat eksogeeniset muuttujat. Tarkastetaan, että näyttää siltä, miltä pitää." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "X = df[['TV', 'radio', 'newspaper']]\n", "y = df.sales" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
TVradionewspaper
1230.137.869.2
244.539.345.1
317.245.969.3
4151.541.358.5
5180.810.858.4
\n", "
" ], "text/plain": [ " TV radio newspaper\n", "1 230.1 37.8 69.2\n", "2 44.5 39.3 45.1\n", "3 17.2 45.9 69.3\n", "4 151.5 41.3 58.5\n", "5 180.8 10.8 58.4" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulostetaan taas ensimmäiset tai viimeiset rivit\n", "X.head()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.frame.DataFrame" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# malli ottaa eksogeeniset muuttujat pandas-datakehyksenä\n", "# tarkastetaan, että tämä pätee\n", "type(X)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(200, 3)" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tsekataan vielä varmuuden vuoksi muoto\n", "X.shape" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1 22.1\n", "2 10.4\n", "3 9.3\n", "4 18.5\n", "5 12.9\n", "Name: sales, dtype: float64" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulosta ensimmäiset tai viimeiset rivit\n", "# huomaathan, että tämä näyttää erilaiselta\n", "y.head()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.series.Series" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tarkastetaan muuttujan tyyppi\n", "# malli hyväksyy endogeenisena muuttujana esim. pandas-sarjoja\n", "type(y)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(200,)" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tarkastetaan taas muuttujan muoto. huomaathan eron X:n muotoon?\n", "y.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ennen kun voit alkaa mallintamaan, sinun täytyy vielä jakaa data harjoitus- ja testijoukkoon. Tuo tätä varten sopivasta kirjastosta tarvittava metodi ja jaa data joukkoihin valmiin menetelmän avulla." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state = 42)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nyt olet valmis aloittamaan mallinnuksen. Aloitat lineaarisella regressiolla. Tuot `sklearn.linear_model`-kirjastosta sopivan menetelmän ja luot malliolion." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "from sklearn.linear_model import LinearRegression\n", "\n", "linreg = LinearRegression()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Seuraavaksi malli täytyy sovittaa harjoitusdataan ennusteiden tekemistä varten." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "linreg.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pohdit, että oma osasto saattaisi olla kiinnostunut tietämään mainontakanavan vaikutuksesta myyntiin. Stackoverflow:ssa neuvotaan, miten kertoimien arvot saa esiin mallista, joten päätät selvittää asian." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2.778303460245283" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulosta vakion arvo\n", "linreg.intercept_" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "# tee vektori, johon tulee muuttujien nimet. \n", "# huolehdi siitä, että järjestys on sama kuin datakehyksessä\n", "# muuttujien nimet voi kääntää suomeksi, jos haluaa\n", "coef_names = ['TV', 'radio', 'sanomalehti']" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('TV', 0.045433558624649886),\n", " ('radio', 0.1914565356174138),\n", " ('sanomalehti', 0.0025680908157006068)]" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# kerätään muuttujat pareittain listaksi ja tulostetaan lista\n", "coefs = zip(coef_names, linreg.coef_)\n", "coefs = list(coefs)\n", "\n", "coefs" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# visualisoidaan kertoimia horisontaalisen pylväsdigrammin avulla\n", "plt.barh(y = X.columns, width = linreg.coef_, height = 0.4)\n", "plt.title(\"Lineaarisen regression kertoimien arvot\", fontsize = 14)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Haluat saada paremman kuvan siitä, miten malli toimii, joten valitset yksittäisiä arvoja testijoukosta ja tuotat niille ennusteen." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([16.38348211, 20.92434957, 21.61495426])" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# kutsu sopivaa metodia\n", "linreg.predict(X_test[0:3])" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "96 16.9\n", "16 22.4\n", "31 21.4\n", "Name: sales, dtype: float64" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tarkasta vastaavat toteutuneet myynnin arvot ja vertaa näitä ennusteisiin\n", "y_test[0:3]" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
TVradionewspaper
96163.331.652.9
16195.447.752.9
31292.928.343.2
\n", "
" ], "text/plain": [ " TV radio newspaper\n", "96 163.3 31.6 52.9\n", "16 195.4 47.7 52.9\n", "31 292.9 28.3 43.2" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# voit myös tarkastaa markkinointikustannukset eri kanavien osalta \n", "# ja miettiä näiden välisiä eroja\n", "X_test[0:3]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Seuraavaksi ennustat myynnin koko testijoukolle ja piirrät kuvan, jonka avulla voit verrata mallin antamia ennusteita todelliseen myyntiin." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "# valitse sopiva metodi ja argumentti\n", "pred = linreg.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.8935163320163659" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# valitse sopiva metodi, joka antaa mallin selitysasteen ja tarvittavat argumentit\n", "linreg.score(X_test, y_test)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# piirretään kuva mallin antamista ennusteista ja todellisista arvoista\n", "plt.plot(y_test, pred, '.')\n", "plt.plot([5, 25], [5, 25], linestyle='--', color = 'red', label = \"oikea arvaus\")\n", "plt.xlim([5.0, 25.0]), plt.ylim([5.0, 25.0])\n", "\n", "plt.title(\"Lineaarisen regression ennuste\", fontsize = 14)\n", "plt.xlabel('Todellinen myynti', fontsize = 14)\n", "plt.ylabel('Mallin ennustama myynti', fontsize = 14)\n", "plt.legend(loc = 4, fontsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pohdit, ovatko kaikki muuttujasi todella tarpeellisia mallissasi. Pelkäät, että mallisi saattaisi ylisovittaa testidataasi ja päätät siksi turvautua regression säätelymenetelmiin. Aloitat lasso-regressiomallilla." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "# hae sopiva kirjasto ja luo malliolio\n", "from sklearn.linear_model import Lasso\n", "lasso = Lasso()" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,\n", " normalize=False, positive=False, precompute=False, random_state=None,\n", " selection='cyclic', tol=0.0001, warm_start=False)" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# sovita malli harjoitusdatalla\n", "lasso.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Muistat, että lasso rankaisee mallia positiivisten kertoimien määrästä. Päätät tulostaa kertoimiesi arvon tarkkaillaksesi tilannetta." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2.923315802134388" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulosta vakion arvo\n", "lasso.intercept_" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('TV', 0.045328390959992436),\n", " ('radio', 0.1876370210125412),\n", " ('sanomalehti', 0.0012818048351305234)]" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# kerätään muuttujien kertoimet listaksi ja tulostetaan lista\n", "coefs = zip(coef_names, lasso.coef_)\n", "coefs = list(coefs)\n", "\n", "coefs" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# piirretään vielä kuva\n", "plt.barh(y = X.columns, width = lasso.coef_, height = 0.4)\n", "plt.title(\"Lasso regression kertoimien arvot\", fontsize = 14)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Seuraavaksi on aika ennustaa malli koko harjoitusdatalla ja tarkastella sen antaman ennusteen luotettavuutta." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "# sijoita mallioliolle sopiva metodi, jolla saat ennusteet koko testijoukolle \n", "pred = lasso.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.8951947205229303" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulosta mallin selitysaste\n", "lasso.score(X_test, y_test)" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# piirretään vielä mallin ennustama myynti verrattuna todelliseen myyntiin\n", "plt.plot(y_test, pred, '.')\n", "plt.plot([5, 25], [5, 25], linestyle='--', color = 'red', label = \"oikea arvaus\")\n", "plt.xlim([5.0, 25.0]), plt.ylim([5.0, 25.0])\n", "\n", "plt.title(\"Lasso regression ennuste\", fontsize = 14)\n", "plt.xlabel('Todellinen myynti', fontsize = 14)\n", "plt.ylabel('Mallin ennustama myynti', fontsize = 14)\n", "plt.legend(loc = 4, fontsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Haluat myös varmistaa, ettei mallisi anna liian suurta painoarvoa millekään yhdelle muuttujalle. Tämän varmistamiseksi kehität vielä mallin harjanneregressio-menetelmällä." ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "# hae sopiva kirjasto ja luo malliolio\n", "from sklearn.linear_model import Ridge\n", "ridge = Ridge()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,\n", " normalize=False, random_state=None, solver='auto', tol=0.001)" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# sovita malli\n", "ridge.fit(X_train, y_train)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2.778406459190581" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulosta vakio\n", "ridge.intercept_" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('TV', 0.04543356062619907),\n", " ('radio', 0.191449789195967),\n", " ('sanomalehti', 0.002569903732349179)]" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulostetaan kertoimet\n", "coefs = zip(coef_names, ridge.coef_)\n", "coefs = list(coefs)\n", "\n", "coefs" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# piirretään kuva\n", "plt.barh(y = X.columns, width = ridge.coef_, height = 0.4)\n", "plt.title(\"Ridge regression kertoimien arvot\", fontsize = 14)\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.8935173307476478" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulostetaan mallin selitysaste\n", "ridge.score(X_test, y_test)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ennustetaan malli koko datasetille ja tarkastetaan selitysaste." ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": [ "# valitse sopiva menetelmä mallioliolle\n", "pred = ridge.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# piirretään kuva\n", "plt.plot(y_test, pred, '.')\n", "plt.plot([5, 25], [5, 25], linestyle='--', color = 'red', label = \"oikea arvaus\")\n", "plt.xlim([5.0, 25.0]), plt.ylim([5.0, 25.0])\n", "\n", "plt.title(\"Ridge regression ennuste\", fontsize = 14)\n", "plt.xlabel('Todellinen myynti', fontsize = 14)\n", "plt.ylabel('Mallin ennustama myynti', fontsize = 14)\n", "plt.legend(loc = 4, fontsize = 12)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Piirretään mallien kertoimet samaan kuvaan, jotta saadaan käsitys siitä, miten sääntely vaikuttaa." ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ind = np.arange(3)\n", "\n", "fig, ax = plt.subplots()\n", "\n", "ax.barh(y = ind - 0.2, width = linreg.coef_, height = 0.2, \n", " label = \"Lineaarinen\", color = 'r')\n", "ax.barh(y = ind, width = lasso.coef_, height = 0.2, \n", " label = \"Lasso\", color = 'g')\n", "\n", "ax.barh(y = ind + 0.2, width = ridge.coef_, height = 0.2, \n", " label = \"Ridge\", color = 'b')\n", "\n", "ax.legend(loc = 4, fontsize = 12)\n", "ax.set_title(\"Kertoimien arvojen vertailu\", fontsize = 14)\n", "ax.set(yticks = ind + 0.2, yticklabels = coef_names, ylim = [0.4 - 1, 3])\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Myyntiosastolta toivotaan arvioita siitä, kuinka luotettavaksi arviot ennusteesi. Haluat pelata varman päälle ja tarkastaa ennusteesi ristiinvalidointimenetelmän avulla. Pohdit myös, että myyntiosasto arvostaisi erityisesti rahamääräistä arviota. Päätät siis arvioida mallisi tulosta neliövirheen neliöjuuren avulla. Tämä antaa rahamääräisen arvion mallisi mittavirheestä." ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import cross_validate" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [], "source": [ "# laske vektori, jossa on ristiinvalidoinnin tulokset\n", "# valitse haluamasi määrä kierroksia ja sopiva menetelmä\n", "cv_tulokset = cross_validate(linreg, X, y, cv = 10, scoring = 'neg_mean_squared_error',\n", " return_train_score = True)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['fit_time', 'score_time', 'test_score', 'train_score']" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# seuraavasta saat muistikirjaasi yllä luomasi vektorin sisällön\n", "sorted(cv_tulokset.keys())" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([-3.56038438, -3.29767522, -2.08943356, -2.82474283, -1.3027754 ,\n", " -1.74163618, -8.17338214, -2.11409746, -3.04273109, -2.45281793])" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tulosta oikea tunnusluku\n", "cv_tulokset['test_score']" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3.0599676181185136" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# laske tunnusluvulle keskiarvo\n", "mse_linreg = - cv_tulokset['test_score'].mean()\n", "mse_linreg" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.749276312684338" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# nyt sinulla on neliövirhe, vielä pitää laskea neliöjuuri\n", "rmse_linreg = np.sqrt(mse_linreg)\n", "rmse_linreg" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "14.022500000000003" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# laske vielä vertailun vuoksi myynnin keskiarvo datasta\n", "# tästä saat käsityksen siitä, onko mittavirhe suuri vai pieni\n", "y.mean()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Toistetaan analyysi lasso-regressiolle" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import cross_val_score" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([-3.40281859, -3.34293038, -2.19117817, -2.7260759 , -1.2883128 ,\n", " -1.72487503, -7.92226606, -2.08887591, -3.16633334, -2.43095955])" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# valitse muuttujat sekä sopiva menetelmä\n", "# valitse sama määrä ristiinvalidointikierroksia kun edellisellä kerralla\n", "scores = cross_val_score(lasso, X, y, cv = 10, scoring = 'neg_mean_squared_error')\n", "scores" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.7402478477470635" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# lasketaan keskiarvo ja otetaan neliöjuuri\n", "rmse_lasso = np.sqrt(- scores.mean())\n", "rmse_lasso" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Viimeisenä tehtävänäsi on laskea virhearvio harjanneregressiolle ja vertailla malleja, jotta voit päättää, minkä malleista esittelet myyntiosastolle." ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([-3.56031324, -3.29774029, -2.08953325, -2.82465373, -1.30277689,\n", " -1.74162784, -8.1731499 , -2.11408297, -3.04288893, -2.45280786])" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# valitse sama määrä ristiinvalidointikierroksia kun edellisissä\n", "scores = cross_val_score(ridge, X, y, cv = 10, scoring = 'neg_mean_squared_error')\n", "scores" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.749273418013899" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rmse_ridge = np.sqrt(- scores.mean())\n", "rmse_ridge" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Näppituntumasi sanoo, että mallisi pärjäävät melko hyvin. Päätät vielä piirtää kuvan kaikkien mallien antamista mittavirheistä. Ajattelet, että tämä kuva auttaa sinua havainnollistamaan myyntiosastolle, että olet tehnyt huolellista työtä ja tarkastellut useita malleja, jotka antavat samansuuntaisen tuloksen." ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.barh(y = ['Lineaarinen', 'Lasso', 'Ridge'], \n", " width = [rmse_linreg, rmse_lasso, rmse_ridge], \n", " height = 0.4)\n", "\n", "plt.xlim([1.735, 1.755])\n", "plt.title(\"Mittavirheiden vertailu mallien välillä\", fontsize = 14)\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Lisätehtävä" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "1. Kuinka yleiseksi arvioisit mallisi? Voidaanko myynnin määrää lisätä aina lisäämällä markkinointiin käytettäviä kustannuksia?\n", "2. Kannattaako yrityksen käyttää vain yhtä markkinointikanavaa vai valita useita? Antaako mallisi vastauksen tähän kysymykseen. Miksi ja miksi ei?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 2 }