Demand-Driven Associative Classification
05.2011β―Π³. Β· Springer Science & Business Media
ΠΠ»Π΅ΠΊΡΡΠΎΠ½Π½Π° ΠΊΠ½ΠΈΠ³Π°
112
Π‘ΡΡΠ°Π½ΠΈΡΠΈ
ΠΡΠΈΡΠΊΠΎ Π·Π° ΡΠ°Π·ΠΈ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½Π° ΠΊΠ½ΠΈΠ³Π°
The ultimate goal of machines is to help humans to solve problems.
Such problems range between two extremes: structured problems for which the solution is totally defined (and thus are easily programmed by humans), and random problems for which the solution is completely undefined (and thus cannot be programmed). Problems in the vast middle ground have solutions that cannot be well defined and are, thus, inherently hard to program. Machine Learning is the way to handle this vast middle ground, so that many tedious and difficult hand-coding tasks would be replaced by automatic learning methods. There are several machine learning tasks, and this work is focused on a major one, which is known as classification. Some classification problems are hard to solve, but we show that they can be decomposed into much simpler sub-problems. We also show that independently solving these sub-problems by taking into account their particular demands, often leads to improved classification performance.
Such problems range between two extremes: structured problems for which the solution is totally defined (and thus are easily programmed by humans), and random problems for which the solution is completely undefined (and thus cannot be programmed). Problems in the vast middle ground have solutions that cannot be well defined and are, thus, inherently hard to program. Machine Learning is the way to handle this vast middle ground, so that many tedious and difficult hand-coding tasks would be replaced by automatic learning methods. There are several machine learning tasks, and this work is focused on a major one, which is known as classification. Some classification problems are hard to solve, but we show that they can be decomposed into much simpler sub-problems. We also show that independently solving these sub-problems by taking into account their particular demands, often leads to improved classification performance.
The ultimate goal of machines is to help humans to solve problems.
Such problems range between two extremes: structured problems for which the solution is totally defined (and thus are easily programmed by humans), and random problems for which the solution is completely undefined (and thus canno...
ΠΡΠΊΡΠΈΠΉΡΠ΅ ΠΎΡΠ΅
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ΠΠ½ΡΡΠ°Π»ΠΈΡΠ°ΠΉΡΠ΅ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΠ΅ΡΠΎ Google Play ΠΠ½ΠΈΠ³ΠΈ Π·Π° Android ΠΈ iPad/iPhone. Π’ΠΎ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ½ΠΎ ΡΠ΅ ΡΠΈΠ½Ρ
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ΠΠ°ΠΏΡΠΎΠΏΠΈ ΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠΈ
ΠΠΎΠΆΠ΅ΡΠ΅ Π΄Π° ΡΠ»ΡΡΠ°ΡΠ΅ Π·Π°ΠΊΡΠΏΠ΅Π½ΠΈΡΠ΅ ΠΎΡ Google Play Π°ΡΠ΄ΠΈΠΎΠΊΠ½ΠΈΠ³ΠΈ ΠΏΠΎΡΡΠ΅Π΄ΡΡΠ²ΠΎΠΌ ΡΠ΅Π± Π±ΡΠ°ΡΠ·ΡΡΠ° Π½Π° ΠΊΠΎΠΌΠΏΡΡΡΡΠ° ΡΠΈ.
ΠΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈ ΡΠ΅ΡΡΠΈ ΠΈ Π΄ΡΡΠ³ΠΈ ΡΡΡΡΠΎΠΉΡΡΠ²Π°
ΠΠ° Π΄Π° ΡΠ΅ΡΠ΅ΡΠ΅ Π½Π° ΡΡΡΡΠΎΠΉΡΡΠ²Π° Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎ ΠΌΠ°ΡΡΠΈΠ»ΠΎ, ΠΊΠ°ΡΠΎ Π½Π°ΠΏΡΠΈΠΌΠ΅Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡΠ΅ ΡΠ΅ΡΡΠΈ ΠΎΡ Kobo, ΡΡΡΠ±Π²Π° Π΄Π° ΠΈΠ·ΡΠ΅Π³Π»ΠΈΡΠ΅ ΡΠ°ΠΉΠ» ΠΈ Π΄Π° Π³ΠΎ ΠΏΡΠ΅Ρ
Π²ΡΡΠ»ΠΈΡΠ΅ Π½Π° ΡΡΡΡΠΎΠΉΡΡΠ²ΠΎΡΠΎ ΡΠΈ. ΠΠ·ΠΏΡΠ»Π½Π΅ΡΠ΅ ΠΏΠΎΠ΄ΡΠΎΠ±Π½ΠΈΡΠ΅ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΠΈ Π² ΠΠΎΠΌΠΎΡΠ½ΠΈΡ ΡΠ΅Π½ΡΡΡ, Π·Π° Π΄Π° ΠΏΡΠ΅Ρ
Π²ΡΡΠ»ΠΈΡΠ΅ ΡΠ°ΠΉΠ»ΠΎΠ²Π΅ΡΠ΅ Π² ΠΏΠΎΠ΄Π΄ΡΡΠΆΠ°Π½ΠΈΡΠ΅ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈ ΡΠ΅ΡΡΠΈ.
