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Refinado por: Nome da Publicação: Machine Learning remover
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1
Engineering problems in machine learning systems
Engineering problems in machine learning systems
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Engineering problems in machine learning systems

Kuwajima, Hiroshi ; Yasuoka, Hirotoshi ; Nakae, Toshihiro

Machine learning, 2020-05, Vol.109 (5), p.1103-1126 [Periódico revisado por pares]

New York: Springer US

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2
Special issue on feature engineering editorial
Special issue on feature engineering editorial
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Special issue on feature engineering editorial

Verdonck, Tim ; Baesens, Bart ; Óskarsdóttir, María ; vanden Broucke, Seppe

Machine learning, 2024-07, Vol.113 (7), p.3917-3928 [Periódico revisado por pares]

New York: Springer US

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3
Coefficient tree regression: fast, accurate and interpretable predictive modeling
Coefficient tree regression: fast, accurate and interpretable predictive modeling
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Coefficient tree regression: fast, accurate and interpretable predictive modeling

Sürer, Özge ; Apley, Daniel W. ; Malthouse, Edward C.

Machine learning, 2024-07, Vol.113 (7), p.4723-4759 [Periódico revisado por pares]

New York: Springer US

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4
VEST: automatic feature engineering for forecasting
VEST: automatic feature engineering for forecasting
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VEST: automatic feature engineering for forecasting

Cerqueira, Vitor ; Moniz, Nuno ; Soares, Carlos

Machine learning, 2024-07, Vol.113 (7), p.4523-4545 [Periódico revisado por pares]

New York: Springer US

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5
Forecasting electricity consumption by aggregating specialized experts: A review of the sequential aggregation of specialized experts, with an application to Slovakian and French country-wide one-day-ahead (half-)hourly predictions
Forecasting electricity consumption by aggregating specialized experts: A review of the sequential aggregation of specialized experts, with an application to Slovakian and French country-wide one-day-ahead (half-)hourly predictions
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Forecasting electricity consumption by aggregating specialized experts: A review of the sequential aggregation of specialized experts, with an application to Slovakian and French country-wide one-day-ahead (half-)hourly predictions

Devaine, Marie ; Gaillard, Pierre ; Goude, Yannig ; Stoltz, Gilles

Machine learning, 2013-02, Vol.90 (2), p.231-260 [Periódico revisado por pares]

Boston: Springer US

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6
Relational data embeddings for feature enrichment with background information
Relational data embeddings for feature enrichment with background information
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Relational data embeddings for feature enrichment with background information

Cvetkov-Iliev, Alexis ; Allauzen, Alexandre ; Varoquaux, Gaël

Machine learning, 2023-02, Vol.112 (2), p.687-720 [Periódico revisado por pares]

New York: Springer US

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7
Learning from multiple annotators with varying expertise
Learning from multiple annotators with varying expertise
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Learning from multiple annotators with varying expertise

Yan, Yan ; Rosales, Rómer ; Fung, Glenn ; Subramanian, Ramanathan ; Dy, Jennifer

Machine learning, 2014-06, Vol.95 (3), p.291-327 [Periódico revisado por pares]

New York: Springer US

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8
A process for predicting manhole events in Manhattan
A process for predicting manhole events in Manhattan
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A process for predicting manhole events in Manhattan

Rudin, Cynthia ; Passonneau, Rebecca J. ; Radeva, Axinia ; Dutta, Haimonti ; Ierome, Steve ; Isaac, Delfina

Machine learning, 2010-07, Vol.80 (1), p.1-31 [Periódico revisado por pares]

Boston: Springer US

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9
Fraud detection with natural language processing
Fraud detection with natural language processing
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Fraud detection with natural language processing

Boulieris, Petros ; Pavlopoulos, John ; Xenos, Alexandros ; Vassalos, Vasilis

Machine learning, 2023-07 [Periódico revisado por pares]

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10
Analysis of network traffic features for anomaly detection
Analysis of network traffic features for anomaly detection
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Analysis of network traffic features for anomaly detection

Iglesias, Félix ; Zseby, Tanja

Machine learning, 2015-10, Vol.101 (1-3), p.59-84 [Periódico revisado por pares]

New York: Springer US

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