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Machine Learning in Action
3
Machine learning basics
I was eating dinner with a couple when they asked what I was working on recently. I
replied, Machine learning. ” The wife turned ...
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...
... 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...
... succeed in selectin
g
the most appropriate machine
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tanding of the different machine learning paradigms ... processin
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and interpretation of inherent visua
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eatures. In t
h
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ectua
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i
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ormat
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ay
between human and machine...
... 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...
... We then present a machine
learning technique to order the sequence
of events identified in the narratives. We
finally report the results we obtained.
1 Extraction of Temporal Information
and Scene ... 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...
... 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...
...
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