Matches in Nanopublications for { ?s <http://www.w3.org/2000/01/rdf-schema#label> ?o ?g. }
- achieves label "performs the task - A relation between a run and a task, where the run achieves specifications formulated by the task." assertion.
- hasOutput label "has as output" assertion.
- hasOutput label "has as output" assertion.
- hasOutput label "has as output" assertion.
- hasOutput label "has as output" assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasOutput label "has as output - A relation between a run and either a model or model evaluation that is produced on it's output." assertion.
- hasValue label "has the result value" assertion.
- hasValue label "has the result value" assertion.
- hasValue label "has the result value" assertion.
- hasValue label "has the result value" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- hasValue label "has the result value - assigns a numerical value denoting the measured result of an evaluation" assertion.
- realizes label "executes an implementation that implements the algorithm" assertion.
- realizes label "executes an implementation that implements the algorithm" assertion.
- realizes label "executes an implementation that implements the algorithm" assertion.
- realizes label "executes an implementation that implements the algorithm" assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- realizes label "executes an implementation of the algorithm - A relation between a run and an algorithm, where the run executes an implementation of the algorithm." assertion.
- specifiedBy label "measures" assertion.
- specifiedBy label "measures" assertion.
- specifiedBy label "measures" assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- specifiedBy label "measures - A relation between an entity and the information content entity that specifies it." assertion.
- dataset-label label "the name of the dataset" assertion.
- algorithm label "the used algorithm (e.g. Random Forest)" assertion.
- assertion label "Publishing the evaluation result of a Machine Learning experiment" assertion.
- dataset label "the URL of the used dataset" assertion.
- evaluation label "an evaluation" assertion.
- evaluation-measure label "the evaluation measure (e.g. Accuracy)" assertion.
- evaluation-value label "value of the evaluation result (e.g. 0.81 if the accuracy is 81%)" assertion.
- run label "a run" assertion.
- task label "the task performed (e.g. Spam Detection)" assertion.
- hasInput label "uses as input" assertion.
- hasInput label "uses as input" assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- hasInput label "uses as input - A relation between a run and data that is taken as input to the run." assertion.
- dataset-label label "the name of the dataset" assertion.
- algorithm label "the used algorithm (e.g. Random Forest)" assertion.
- assertion label "Publishing the evaluation result of a Machine Learning experiment" assertion.
- dataset label "the URL of the used dataset" assertion.
- evaluation label "an evaluation" assertion.
- evaluation-measure label "the evaluation measure (e.g. Accuracy)" assertion.
- evaluation-value label "value of the evaluation result (e.g. 0.81 if the accuracy is 81%)" assertion.
- run label "this run" assertion.
- task label "the task performed (e.g. Spam Detection)" assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.
- STATO_0000415 label "accuracy - in the context of binary classification, accuracy is defined as the proportion of true results (both true positives and true negatives) to the total number of cases examined (the sum of true positive, true negative, false positive and false negative). It can be understood as a measure of the proximity of measurement results to the true value." assertion.