Difference between revisions of "Test"

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(Three-Layer Precision, Three-Layer Recall, and Three-Layer F1 Score)
(Three-Layer Precision, Three-Layer Recall, and Three-Layer F1 Score)
 
(9 intermediate revisions by the same user not shown)
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''This section needs fixing, it seems there are some problems with the'' math ''command''. See [http://www.tomcollinsresearch.net/mirex-pattern-discovery-task.html#evaluation here] for a working version.
 
''This section needs fixing, it seems there are some problems with the'' math ''command''. See [http://www.tomcollinsresearch.net/mirex-pattern-discovery-task.html#evaluation here] for a working version.
  
<math>F_3</math>
 
  
  
 
Three-layer precision (<math>P_3</math>), three-layer recall (<math>R_3</math>), and three-layer <math>F_1</math> score (<math>F_3</math>) are defined as follows:
 
Three-layer precision (<math>P_3</math>), three-layer recall (<math>R_3</math>), and three-layer <math>F_1</math> score (<math>F_3</math>) are defined as follows:
 
:<math>
 
:<math>
\begin{equation}
 
 
F_3(\Pi, \Xi) = \frac{2 P_3(\Pi, \Xi) R_3(\Pi, \Xi)}{P_3(\Pi, \Xi) + R_3(\Pi, \Xi)},
 
F_3(\Pi, \Xi) = \frac{2 P_3(\Pi, \Xi) R_3(\Pi, \Xi)}{P_3(\Pi, \Xi) + R_3(\Pi, \Xi)},
\end{equation}
 
 
</math>
 
</math>
 
where
 
where
 
:<math>
 
:<math>
\begin{eqnarray}
 
 
P_3(\Pi, \Xi) &=& \frac{1}{n_\mathcal{Q}} \sum_{j = 1}^{n_\mathcal{Q}}
 
P_3(\Pi, \Xi) &=& \frac{1}{n_\mathcal{Q}} \sum_{j = 1}^{n_\mathcal{Q}}
 
\max \{ F_2(\mathcal{P}_i, \mathcal{Q}_j) \mid i = 1,\ldots, n_\mathcal{P} \},\\[.2cm]
 
\max \{ F_2(\mathcal{P}_i, \mathcal{Q}_j) \mid i = 1,\ldots, n_\mathcal{P} \},\\[.2cm]
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P_1(P, Q) &=& |P \cap Q|/|Q|,\\[.2cm]
 
P_1(P, Q) &=& |P \cap Q|/|Q|,\\[.2cm]
 
R_1(P, Q) &=& |P \cap Q|/|P|.
 
R_1(P, Q) &=& |P \cap Q|/|P|.
\end{eqnarray}
 
 
</math>
 
</math>

Latest revision as of 13:57, 13 August 2013

Three-Layer Precision, Three-Layer Recall, and Three-Layer F1 Score

This section needs fixing, it seems there are some problems with the math command. See here for a working version.


Three-layer precision (), three-layer recall (), and three-layer score () are defined as follows:

where

Failed to parse (syntax error): {\displaystyle P_3(\Pi, \Xi) &=& \frac{1}{n_\mathcal{Q}} \sum_{j = 1}^{n_\mathcal{Q}} \max \{ F_2(\mathcal{P}_i, \mathcal{Q}_j) \mid i = 1,\ldots, n_\mathcal{P} \},\\[.2cm] R_3(\Pi, \Xi) &=& \frac{1}{n_\mathcal{P}} \sum_{i = 1}^{n_\mathcal{P}} \max \{ F_2(\mathcal{P}_i, \mathcal{Q}_j) \mid j = 1,\ldots, n_\mathcal{Q} \},\\[.2cm] F_2(\mathcal{P}, \mathcal{Q}) &=& \frac{2 P_2(\mathcal{P}, \mathcal{Q}) R_2(\mathcal{P}, \mathcal{Q})} {P_2(\mathcal{P}, \mathcal{Q}) + R_2(\mathcal{P}, \mathcal{Q})},\\[.2cm] P_2(\mathcal{P}, \mathcal{Q}) &=& \frac{1}{m_Q} \sum_{l = 1}^{m_Q} \max \{ F_1(P_k, Q_l) \mid k = 1,\ldots, m_P \},\\[.2cm] R_2(\mathcal{P}, \mathcal{Q}) &=& \frac{1}{m_P} \sum_{k = 1}^{n_P} \max \{ F_1(P_k, Q_l) \mid l = 1,\ldots, m_Q \},\\[.2cm] F_1(P, Q) &=& \frac{2 P_1(P, Q) R_1(P, Q)}{P_1(P, Q) + R_1(P, Q)},\\[.2cm] P_1(P, Q) &=& |P \cap Q|/|Q|,\\[.2cm] R_1(P, Q) &=& |P \cap Q|/|P|. }