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... crucial in scientific
discovery’, the pioneering work by Swanson on hypo-
thesis generation [299] is mainly credited with sparking
interest in text mining techniques in biology. Text
mining aids in ... 885
profiling data using machine learning. Plant Physiol
126, 943–951.
68 Kell DB (2002) Metabolomics and machine learning:
explanatory analysis of complex metabolome data
using ge...
... and contains edges present either
in G or in G
but not in both.
5
Called also ring sum.
6
Where \ is the set minus operation and is interpreted as removing elements from X that
are in Y .
Multiresolution ... sampling points can be represented explicitly, too:
in this case the sampling grid is represented by a graph consisting of vertices cor-
responding to the sampling points and...
...
Machine learning basics 3
1.1 What is machine learning? 5
Sensors and the data deluge 6
■
Machine learning will be more
important in the future 7
1.2 Key terminology 7
1.3 Key tasks of machine ... w1 h4" alt=""
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Machine learning basics
I was eating dinner with a couple when they asked what I was working on recently. I
replied, Machine le...
... classification
training data. 2,000 articles containing smiles and
2,000 articles containing frowns were held-out as
optimising test data. We took increasing amounts
of articles from the remaining dataset ... 22,000 in increments of 1,000, an equal number
being taken from the positive and negative sets) as
optimising training data. For each set of training
data we extracted a context of an i...
... pruning and control settings for RPART
(cp=0.0001, minsplit=20, minbucket=7). All results
reported were obtained by performing 20-fold cross-
validation.
In the prediction phase, the trained ... prede-
fined baseline features. Then we train models com-
bining the baseline with all additional features sep-
arately. We choose the best performing feature (f-
measure according to Vilain et al. (...
... Resolution by Machine
Learning
Since a huge text corpus has become widely
available, the machine- learning approach has
been utilized for some problems in natural lan-
guage processing. The most ... decision-tree learning research to itself.
3.3 Training Attributes
The training attributes that we prepared for
Japanese ellipsis resolution are listed in Table
2. The trainin...
... computer vision algorithms in succinct
algebraic form. For instance, in certain interpolation schemes it becomes necessary to switch from points with
real-valued coordinates (floating point coordinates) ... Neumann’s original automaton [5, 6, 7, 8, 9]. A more general class
of cellular array computers are pyramids and Thinking Machines Corporation’s Connection Machines [10, 11,
12]. I...
... set aside this type of
link.
Subordinate links generally connect signals to
events, for instance to mark polarity by linking a
not to its main verb. We identify these links simul-
taneously with ... VB_GR_COP_INF,
VB_GR_COP_FIN, VB_GR_MOD_INF,
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UNKNOWN.
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... particu-
larly in machine learning. Since these methods have a stronger mathematical
slant than earlier machine learning methods (e.g., neural networks), there
is also significant interest in the statistics ... domain X other
than it being a set. In order to study the problem of learning, we need
additional structure. In learning, we want to be able to generalize to unseen
dat...