From bfad5c71dd6c2e06a617efe412b9d45ddc0fbf57 Mon Sep 17 00:00:00 2001 From: fortierq Date: Fri, 8 Dec 2023 09:43:28 +0000 Subject: [PATCH] deploy: 70fd2524cbcbf8d32dc4ab5d2e2b41160b5f4d29 --- .../apprentissage/tp/tp_voitures/tp_voitures.ipynb | 14 +++++++------- dl/apprentissage/tp/tp_voitures/tp_voitures.html | 10 +++++----- searchindex.js | 2 +- 3 files changed, 13 insertions(+), 13 deletions(-) diff --git a/_sources/dl/apprentissage/tp/tp_voitures/tp_voitures.ipynb b/_sources/dl/apprentissage/tp/tp_voitures/tp_voitures.ipynb index 7689e871..21fb8866 100644 --- a/_sources/dl/apprentissage/tp/tp_voitures/tp_voitures.ipynb +++ b/_sources/dl/apprentissage/tp/tp_voitures/tp_voitures.ipynb @@ -394,22 +394,22 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "1908.0" + "10.984615384615385" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "moyenne(0) # moyenne de cylindrée" + "moyenne(7) # nombre moyen de secondes pour aller de 0 à 100 km/h" ] }, { @@ -458,7 +458,7 @@ "metadata": {}, "source": [ "````{admonition} Question\n", - " Définir une variable `X` qui contient les caractéristiques standardisées des voitures.\n", + " Définir une matrice `X` qui contient les caractéristiques standardisées des voitures.\n", "````" ] }, @@ -496,7 +496,7 @@ "metadata": {}, "source": [ "````{admonition} Question\n", - " On aura aussi besoin de réaliser l'opération inverse de la précédente. Écrire une fonction `inverse_standardisation(y)` qui renvoie une liste `x` telle que $x_i = y_i \\sigma_i + \\mu_i$, où $\\mu_i$ et $\\sigma_i$ sont la moyenne et l'écart-type de l'attribut $i$.\n", + " On aura aussi besoin de réaliser l'opération inverse de la précédente. Écrire une fonction `inverse_standardisation(y)` qui, pour une voiture `y` (c'est-à-dire la liste de ses attributs), renvoie une liste `x` telle que $x_i = y_i \\sigma_i + \\mu_i$, où $\\mu_i$ et $\\sigma_i$ sont la moyenne et l'écart-type de l'attribut $i$.\n", "````" ] }, @@ -517,7 +517,7 @@ } ], "source": [ - "inverse_standardisation(X[0]) # égal à attributs[0]" + "inverse_standardisation(X[0]) # doit être égal à attributs[0]" ] }, { diff --git a/dl/apprentissage/tp/tp_voitures/tp_voitures.html b/dl/apprentissage/tp/tp_voitures/tp_voitures.html index c9fdd9f5..a8914c47 100644 --- a/dl/apprentissage/tp/tp_voitures/tp_voitures.html +++ b/dl/apprentissage/tp/tp_voitures/tp_voitures.html @@ -962,12 +962,12 @@

Standardisation des données
-
moyenne(0) # moyenne de cylindrée
+
moyenne(7) # nombre moyen de secondes pour aller de 0 à 100 km/h
-
1908.0
+
10.984615384615385
@@ -993,7 +993,7 @@

Standardisation des données

Question

-

Définir une variable X qui contient les caractéristiques standardisées des voitures.

+

Définir une matrice X qui contient les caractéristiques standardisées des voitures.

@@ -1017,11 +1017,11 @@

Standardisation des données

Question

-

On aura aussi besoin de réaliser l’opération inverse de la précédente. Écrire une fonction inverse_standardisation(y) qui renvoie une liste x telle que \(x_i = y_i \sigma_i + \mu_i\), où \(\mu_i\) et \(\sigma_i\) sont la moyenne et l’écart-type de l’attribut \(i\).

+

On aura aussi besoin de réaliser l’opération inverse de la précédente. Écrire une fonction inverse_standardisation(y) qui, pour une voiture y (c’est-à-dire la liste de ses attributs), renvoie une liste x telle que \(x_i = y_i \sigma_i + \mu_i\), où \(\mu_i\) et \(\sigma_i\) sont la moyenne et l’écart-type de l’attribut \(i\).

-
inverse_standardisation(X[0]) # égal à attributs[0]
+
inverse_standardisation(X[0]) # doit être égal à attributs[0]
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Monplaisir","Cours","TP","Ressources","Cours : Dictionnaire","TP plus proches voisins : Classification des survivants du 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