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initial commit
authorMart Lubbers <mart@martlubbers.net>
Mon, 12 Sep 2016 13:26:01 +0000 (15:26 +0200)
committerMart Lubbers <mart@martlubbers.net>
Mon, 12 Sep 2016 13:26:01 +0000 (15:26 +0200)
.gitignore [new file with mode: 0644] patch | blob
week3/Makefile [new file with mode: 0644] patch | blob
week3/eml.tex [new file with mode: 0644] patch | blob
week3/lobtlb_nnvb.csv [new file with mode: 0644] patch | blob
week3/lobtlb_nnvb_cleaned.csv [new file with mode: 0644] patch | blob

diff --git a/.gitignore b/.gitignore
new file mode 100644 (file)
index 0000000..debc120
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,3 @@
+*.aux
+*.pdf
+*.log
diff --git a/week3/Makefile b/week3/Makefile
new file mode 100644 (file)
index 0000000..feeddb6
--- /dev/null
+++ b/week3/Makefile
@@ -0,0 +1,11 @@
+DOCUMENTS:=eml
+PDFLATEXFLAGS:=-halt-on-error
+PDFLATEX:=pdflatex $(PDFLATEXFLAGS)
+
+all: $(addsuffix .pdf,$(DOCUMENTS))
+
+%.pdf: %.tex
+       pdflatex $<
+
+clean:
+       $(RM) -v $(addprefix $(DOCUMENTS),.pdf .log .aux)
diff --git a/week3/eml.tex b/week3/eml.tex
new file mode 100644 (file)
index 0000000..5e13726
--- /dev/null
+++ b/week3/eml.tex
@@ -0,0 +1,74 @@
+\documentclass[a4paper]{article}
+
+\usepackage{amssymb}
+\usepackage{booktabs}
+\usepackage{float}
+\usepackage{geometry}
+
+\title{Exercise: Machine Learning}
+\author{Mart Lubbers}
+\date{\today}
+
+\begin{document}
+\maketitle
+\subsection*{Chapter 5: Machine Learning}
+\begin{table}[H]
+       \centering
+       \begin{tabular}{lll}
+               \toprule
+               Method & Correctly classified & Root relative squared error\\
+               \midrule
+               NaiveBayes & $96.6449\%$ & $35.7222\%$\\
+               NaiveBayes (10FCF) & $96.4352\%$ & $37.1926\%$\\
+               J48 & $96.6449\%$ & $34.9136\%$\\
+               J48 (10FCF) & $96.4352\%$ & $36.5122\%$\\
+               \bottomrule
+       \end{tabular}
+       \caption{Results for \texttt{P1D} and \texttt{FD}}
+\end{table}
+
+\begin{table}[H]
+       \centering
+       \begin{tabular}{lllllll}
+               \toprule
+               \texttt{P2D} & \texttt{P1D} & \texttt{N2D} & \texttt{N1D} & \texttt{FW} & Correctly classified\\
+               \midrule
+               \checkmark{}    & \checkmark{}  & \checkmark{}  & \checkmark{}  & \checkmark{}  & $98.3225\%$\\
+               \checkmark{}    & \checkmark{}  & \checkmark{}  & \checkmark{}  &       & $97.3905\%$\\
+               \checkmark{}    & \checkmark{}  &       & \checkmark{}  & \checkmark{}  & $98.5555\%$\\
+               \checkmark{}    & \checkmark{}  &       & \checkmark{}  &       & $97.507\%$\\
+               \checkmark{}    & \checkmark{}  &       &       & \checkmark{}  & $98.0429\%$\\
+               \checkmark{}    & \checkmark{}  &       &       &       & $95.5732\%$\\
+
+                       & \checkmark{}  & \checkmark{}  & \checkmark{}  & \checkmark{}  & $\%$\\
+                       & \checkmark{}  & \checkmark{}  & \checkmark{}  &       & $\%$\\
+                       & \checkmark{}  &       & \checkmark{}  & \checkmark{}  & $\%$\\
+                       & \checkmark{}  &       & \checkmark{}  &       & $\%$\\
+                       & \checkmark{}  &       &       & \checkmark{}  & $98.2992\%$\\
+                       & \checkmark{}  &       &       &       & $96.6449\%$\\
+
+                       &       & \checkmark{}  & \checkmark{}  & \checkmark{}  & $\%$\\
+                       &       & \checkmark{}  & \checkmark{}  &       & $\%$\\
+                       &       &       & \checkmark{}  & \checkmark{}  & $\%$\\
+                       &       &       & \checkmark{}  &       & $\%$\\
+                       &       &       &       & \checkmark{}  & $88.4436\%$\\
+
+               \bottomrule
+       \end{tabular}
+       \caption{NaiveBayes}
+\end{table}
+
+\subsection*{Chapter 6: Exercises}
+\begin{itemize}
+       \item\emph{If we look at the Viterbi algorithm, we see that the
+               probability of state at a given position is calculated $n$ the basis of
+               the preceding $n$ states. However, it is claimed that the algorithm
+               takes into account the whole sequence. Explain in your own words (at
+               most $100$) how the probability is influenced by the rest of the
+               sequence, i.e.\ both the positions more than n back and the following
+               positions.}
+
+       \item\emph{Explain in your own words (at most 50) how the EM algorithm
+               works. I don't mean the mathematics, but the underlying concept.}
+\end{itemize}
+\end{document}
diff --git a/week3/lobtlb_nnvb.csv b/week3/lobtlb_nnvb.csv
new file mode 100644 (file)
index 0000000..7abe67a
--- /dev/null
+++ b/week3/lobtlb_nnvb.csv
@@ -0,0 +1,4293 @@
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diff --git a/week3/lobtlb_nnvb_cleaned.csv b/week3/lobtlb_nnvb_cleaned.csv
new file mode 100644 (file)
index 0000000..d087750
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+VB,ATI,IN,JJ,need,NN
+VB,ATI,SPER,<O>,matter,NN
+JJ,NN,MD,VB,force,NN
+VB,ATI,SCOM,CC,bet,NN
+VB,ATI,IN,AT,matter,NN
+VB,ATI,IN,AT,matter,NN
+VB,ATI,VB,RP,fire,NN
+VB,ATI,RP,SCOM,fire,NN
+VB,ATI,IN,ATI,need,NN
+VB,IN,IN,NR,force,NN
+VB,ATI,IN,ABL,need,NN
+VB,PPG,SPER,<O>,taste,NN
+IN,PPG,TO,VB,shop,NN
+VB,ATI,IN,NP,mind,NN
+RP,AT,TO,VB,force,NN
+NNS,AT,TO,VB,force,NN
+VB,ATI,SPER,SQSC,matter,NN
+VB,ATI,SCOM,CD1,lead,NN
+BEDZ,DTI,TO,VB,need,NN
+VB,IN,TO,VB,force,NN
+VB,AT,IN,ATI,end,NN
+<O>,JJ,SCOM,VB,matter,NN
+DT,JJ,TO,VB,bid,NN
+VB,AT,SPER,<O>,bid,NN
+<O>,AT,TO,VB,move,NN
+GENM,NN,TO,VB,offer,NN
+VB,AT,SPER,<O>,repeat,NN
+VB,ATI,SPER,<O>,play,NN
+VB,ATI,CS,ATI,wish,NN
+VB,PPG,SCOM,VBZ,pick,NN
+VB,PPG,IN,ABN,stand,NN
+ATI,JJ,SCOM,VB,combine,NN
+VB,AT,SQSO,JJ,play,NN
+VB,ATI,IN,NNS,play,NN
+<O>,AT,TO,VB,move,NN
+VB,AT,IN,OD,move,NN
+VB,AT,IN,ATI,look,NN
+JJ,NP,TO,VB,move,NN
+ABN,VB,IN,NP,mention,NN
+VB,ATI,RP,IN,show,NN
+VB,ATI,GENM,JJ,show,NN
+NN,ATI,MD,VB,show,NN
+VB,ATI,IN,ATI,help,NN
+MD,VB,IN,NP,help,NN
1617-S1 - LET-REMA-LCEX19: Introduction to Language and Speech Technology