From 8d06c94cdf409f84b014bd059801d1bc265dce51 Mon Sep 17 00:00:00 2001 From: Christina Theodoridou Date: Tue, 15 Jan 2019 12:36:01 +0200 Subject: [PATCH] minor fixes --- presentation/features_and_preprocessing.tex | 41 +++++++++++--------- presentation/main.pdf | Bin 673121 -> 673158 bytes presentation/main.tex | 5 +-- presentation/models.tex | 16 ++++---- 4 files changed, 33 insertions(+), 29 deletions(-) diff --git a/presentation/features_and_preprocessing.tex b/presentation/features_and_preprocessing.tex index 52bc4f8..2dfe4cb 100644 --- a/presentation/features_and_preprocessing.tex +++ b/presentation/features_and_preprocessing.tex @@ -115,33 +115,38 @@ To flatness ή αλλιώς επιπεδότητα του ήχου, είναι \end{figure} -\section{Προεπεξεργασία} -Για την προεπεξεργασία των δεδομένων, δοκιμάστηκαν διάφορες τεχνικές έτσι ώστε να βρεθεί ο βέλτιστος συνδυασμός μεθόδων. Οι μέθοδοι που δοκιμάστηκαν είναι οι κλιμακοποίηση, κανονικοποίηση, μείωση μεταβλητών (PCA?) και ο συνδυασμός τους μαζί με κάποιες παραμέτρους. Τα αποτελέσματα παρουσιάζονται στον πίνακα \ref{table:tab} -Στην κλιμακοποίηση όλα τα χαρακτηριστικά έχουν μέσο 0 και απόκλιση ίση με 1 ενώ στην κανονικοποίηση, μετατρέπονται οι τιμές τους ώστε να ανήκουν στο εύρος [0,1] +\section{Προεπεξεργασία δεδομένων} +Για την προεπεξεργασία των δεδομένων, δοκιμάστηκαν διάφορες τεχνικές έτσι ώστε να βρεθεί ο βέλτιστος συνδυασμός μεθόδων. Οι τρόποι που δοκιμάστηκαν είναι οι κλιμακοποίηση, κανονικοποίηση, VarianceThreshold, PercentileSelection και ο συνδυασμός τους μαζί με την αλλαγή κάποιων παραμέτρων. Τα αποτελέσματα παρουσιάζονται στον πίνακα \ref{table:tab} +Στην κλιμακοποίηση όλα τα χαρακτηριστικά έχουν μέσο 0 και απόκλιση ίση με 1 ενώ στην κανονικοποίηση, μετατρέπονται οι τιμές τους ώστε να ανήκουν στο εύρος [0,1]. Στο VarianceThreshold και PercentileSelection, που είναι συναρτήσεις της βιβλιοθήκης feature\_selection της sklearn, γίνεται μείωση χαρακτηριστικών. Στο VarianceThreshold, η μείωση γίνεται με όρους διακύμανσης, δηλαδή +αφαιρεί όλα τα χαρακτηριστικά των οποίων η διακύμανση δεν ξεπερνά κάποιο κατώφλι, ενώ η PercentileSelection καταργεί όλα τα ποσοστά των χαρακτηριστικών, εκτός από αυτά με καθορισμένο από το χρήστη καλύτερη ποσοστιαία κατάταξη . % removes all but a user-specified highest scoring percentage of features -> better translate? \begin{table}[H] \begin{tabular}{|l|l|l|} \hline -\textbf{Μέθοδος} & \textbf{Τρόπος προεπεξεργασίας} & \textbf{Ακρίβεια} \\ \hline - & Χωρίς προεπεξεργασία & 0.49 \\ \cline{2-3} - & Κλιμακοποίηση & \textbf{0.89} \\ \cline{2-3} - & Κανονικοποίηση & 0.49 \\ \cline{2-3} - & Κλιμακοποίηση και μετά κανονικοποίηση & 0.78 \\ \cline{2-3} - & Μείωση μεταβλητών και κλιμακοποίηση & 0.88 \\ \cline{2-3} - & perReduced Dataset(?) και κλιμακοποίηση & 0.81 \\ \cline{2-3} - & Μείωση μεταβλητών, κλιμακοποίηση και gamma=scale & 0.88 \\ \cline{2-3} - & Μείωση μεταβλητών, κλιμακοποίηση και sigmoid kernel & 0.58 \\ \cline{2-3} -\multirow{-9}{*}{SVM} & Μείωση μεταβλητών, κλιμακοποίηση και poly kernel dgr & 0.84 \\ \hline -Decision Tree & Μείωση μεταβλητών και κλιμακοποίηση & 0.75 \\ \hline -Multi-Layer Perceptron & Μείωση μεταβλητών, κλιμακοποίηση και rndState = 2 & 0.86 \\ \hline -Naive Bayes & Μείωση μεταβλητών και κλιμακοποίηση & 0.65 \\ \hline +\textbf{Μέθοδος} & \textbf{Τρόπος προεπεξεργασίας} & \textbf{Ακρίβεια} \\ \hline + & Χωρίς προεπεξεργασία & 0.49 \\ \cline{2-3} + & Κλιμακοποίηση & 0.89 \\ \cline{2-3} + & Κανονικοποίηση & 0.49 \\ \cline{2-3} + & Κλιμακοποίηση + μετά κανονικοποίηση & 0.78 \\ \cline{2-3} + & VarianceThreshold + κλιμακοποίηση & 0.88 \\ \cline{2-3} + & PercentileSelection + κλιμακοποίηση & 0.81 \\ \cline{2-3} + & VarianceThreshold, κλιμακοποίηση + gamma=scale & 0.88 \\ \cline{2-3} + & VarianceThreshold, κλιμακοποίηση + sigmoid kernel & 0.58 \\ \cline{2-3} +\multirow{-9}{*}{SVM} & VarianceThreshold, κλιμακοποίηση + poly kernel dgr & 0.84 \\ \hline +Decision Tree & VarianceThreshold + κλιμακοποίηση & 0.75 \\ \hline +Multi-Layer Perceptron & VarianceThreshold, κλιμακοποίηση + rndState = 2 & 0.86 \\ \hline +Naive Bayes & VarianceThreshold + κλιμακοποίηση & 0.65 \\ \hline \end{tabular} \caption{Τρόποι προεπεξεργασίας για διάφορα μοντέλα} \label{table:tab} \end{table} -Eπιπλέον, ελέγξαμε όλα τα χαρακτηριστικά ένα προς ένα έτσι ώστε να δούμε εάν υπάρχει τρόπος να φτάσουμε την πλήρη ακρίβεια του μοντέλου μας με λιγότερα ή να φτάσουμε αρκετά κοντά ίσως ακόμα και με μόνο ένα χαρακτηριστικό. -Tα αποτελέσματα έδειξαν ότι κανένα χαρακτηριστικό από μόνο του δεν είναι ικανό να δώσει ικανοποιητικό ποσοστό ακρίβειας στο μοντέλο. Αν πάρουμε το καλύτερο σε όρους ακρίβειας και το δοκιμάσουμε σε συνδυασμό με τα επόμενα καλύτερα, φαίνεται ότι η ακρίβεια αυξάνεται λίγο αλλά όχι αρκετά. +Εν τέλει, αποφασίστηκε να χρησιμοποιηθεί μόνο η κλιμακοποίηση καθώς το κέρδος σε ταχύτητα των παραπάνω τρόπων μείωσης μεταβλητών δεν ήταν αρκετό συγκριτικά με την μείωση της ακρίβειας ώστε να παραμείνουν στην υλοποίηση. Βοήθησαν παρ'όλα αυτά στον προσδιορισμό των χαρακτηριστικών που είναι κάπως καλύτερα από τα άλλα. + + + +Στη συνεχεια, για να γίνει κατανοητό εάν τα χαρακτηριστικά που είναι καλύτερα, είναι ικανά να δώσουν μεγάλο ποσοστό ακρίβειας στο μοντέλο, απομονώθηκαν όλα και ελέχθηκαν ένα ένα. +Tα αποτελέσματα έδειξαν ότι, τελικά, κανένα χαρακτηριστικό από μόνο του δεν είναι ικανό να δώσει ικανοποιητικό ποσοστό ακρίβειας0. Ακόμα και αν πάρουμε το καλύτερο σε όρους ακρίβειας και το δοκιμάσουμε σε συνδυασμό με τα επόμενα καλύτερα, φαίνεται ότι η ακρίβεια αυξάνεται λίγο αλλά όχι αρκετά. 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