Letter: To "My Dear Charles" from John Wesley, January 3, 1741

Digitized from a letter in the Drew University Methodist Collection. 1 Item (2 p.); 17 x 20 cm

Missionary heroes : stories of heroism on the mission field / edited by Charles D. Michael.

http://www.archive.org/details/missionaryheroes00unknuoft

Among the Indians of Alaska. By Charles Replogle ...

http://www.archive.org/details/amongindiansofal00repliala

The life of Father de Smet, S.J. (1801-1873) by E. Laveille, S.J., authorized translation by Marian Lindsay, introduction by Charles Coppens ...

http://www.archive.org/details/lifeoffatherdesm00laverich

Father Pollock and his brother : mission priests of St. Alban's, Birmingham / with a letter from Charles Gore.

http://anglicanhistory.org/bios/pollock/ View document online

An American missionary : a record of the work of Rev. William H. Judge, S.J. / by Charles J. Judge ; introduction by His Eminence, Cardinal Gibbons.

http://www.archive.org/details/anamericanmissio00judguoft

History of Christian missions / by Charles Henry Robinson

http://www.archive.org/details/historyofchristi003076mbp

Additions à la bibliographie de Charles Porset sur les sciences du langage de Port-Royal aux Idéologues (1660-1818)

info:eu-repo/semantics/published

Event models for tumor classification with SAGE gene expression data

Serial Analysis of Gene Expression (SAGE) is a relatively new method for monitoring gene expression levels and is expected to contribute significantly to the progress in cancer treatment by enabling a precise and early diagnosis. A promising application of SAGE gene expression data is classification of tumors. In this paper, we build three event models (the multivariate Bernoulli model, the multinomial model and the normalized multinomial model) for SAGE data classification. Both binary classification and multicategory classification are investigated. Experiments on two SAGE datasets show that the multivariate Bernoulli model performs well with small feature sizes, but the multinomial performs better at large feature sizes, while the normalized multinomial performs well with medium feature sizes. The multinomial achieves the highest overall accuracy.