Sentence examples for negative instance of from inspiring English sources

In Dover, a former Polish neighborhood that is now a haven for Mexican-American strivers, the authors find an entirely negative instance of "intergroup harmony," as white and Latino parents lobby to keep their children from being bused to schools in poor black neighborhoods.

All negative instances of the findings were discussed and accounted for.

Since negative instances of a concept can shed further light on this concept, negative experiences were also sought.

In comparison, we use document-specific keyword frequency to label positive and negative instances of click-words.

To build such a learning system, we needed to specify positive and negative instances of click-words in articles.

Negative instances of false targets were built from the dataset used previously as well as random sequences [ 13, 23].

Assuming inner cluster pairs of expanded forms for each abbreviation to be positive (r = +1) and assuming inter-cluster pairs to be negative (r = −1), we obtained 3678 positive and 19 296 negative instances of the training data for the similarity measure.

In summary, the machine learning approaches performed better than the rule-based approaches in Task A. For example, Team 238 achieved the best performance by using multiple features (bag-of-words, bigram features, section features, topic features, presence of genes) and training a logistic regression model to classify positive vs negative instances of GO evidence sentences.

We applied the unsupervised learning method LDA varying the number of topics n over the dataset L. In order to form the positive instances of topic i we used a threshold of κ1 = 0.02 and to form the negative instances of topic i we used a threshold of κ2 = 0. LDA was applied to a collection of documents in the training set L which contain only the PICO portions of the original document.

To reduce data skewness, we determine the optimal ratio of positive to negative instances on held-out development data, which is composed of 30 randomly chosen training documents.

In order to create the dataset for each experiment, we kept the positive instances and resampled at random N number of negative instances to obtain a new dataset with an imbalance degree of 1-to-N.