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61. Naive Bayes classifier is a simple and effective classification method based on probability theory, but its attribute independence assumption is often violated in the real world.

62. This paper analyzes the shortcomings of Bayes and puts forward a better method to improve it.

63. The misclassification probability of the nearest neighbor decision rule won't exceed 2 times of that of Bayes decision rule when the sample number is very large.

64. For implicit temporal expression recognition, witch is also called as Chinese situation analysis. The Bayes Classification is used for Chinese verb classification.

65. Based on the minimum error Bayes decision theory, the authors proposed a new way of image(segmentation).

66. Through the analysis of the composite base price and the introduction to the Bayesian decision, the Bayes theorem is led into determining the quoted price with the composite base price.

67. In order to solve the problem existing in training data sets, present Bayes algorithm is im- proved and an algorithm using unlabeled data to improve the capability of the classifier is proposed.

68. The posterior probability can also be expressed in terms of class-conditional density function and prior probability by the Bayes theorem.

69. But my favoritetomb is that of Thomas Bayes, the eighteenth-century statistician for whomBayesian filtering is named.

70. The second method uses Bayes classifier in the first step and decision tree classifier in the second step.

71. In this paper, we investigate enhancement of naive Bayes classifier using feature weighting technique.

72. The marginal posterior distribution of the parameter in the ARFIMA models is presented by Bayes theorem and the mode of the marginal posterior distribution is choosed as the estimator.

73. Aim at the document image with both Chinese Characters and English characters, this paper present a character segmentation and language discrimination method based on Simple Bayes Classifier.

74. The recognition rates for the handwritten digits and SAR image classification outperform the tradition Bayes classifier.

75. Experimental results show that Bayes classifier is suitable for the transformer fault diagnosis.

76. To tackle the over-segmentation problem, the blobs were merged iteratively with the utilization of Bayes classification rule.

77. The Bayes risk decision - making model is used to eliminate the invalidated computing packages.

78. The origin of the concept of obtaining posterior probabilities with limited information is attributable to Thomas Bayes.

79. The Bayes rule for minimum error and supervised parameter estimation for Gaussian mixture are used to solve the problem of threshold selection and get a good experimental result.

80. In designing Web Classifier, this thesis makes use of Vector Space Model to represent the web text, which improves the performance of Bayes Classifier.

81. I said my good - bayes, arranged for their temporary care and return home.

82. Conventional remote sensing image classification methods are mostly based on Bayes subjective probability theory.

83. The practice indicate that the Planting Decision-making on Cross Bedding of Farming and Animal Husbandary in the East of Inner Mongolia by the Bayes Rule is feasible.

84. There template matching classifier, Bayes classifier a linear function of classification, non - linear classification,[http://sentencedict.com/bayes.html] neural network classifier.

85. Bayes Network is a new inference and express method of uncertain knowledge.

86. The formula of total probability , conditional probability and bayes formula are elementary formulas of probability theory.

87. In this paper, a Bayes decision rule is derived for the scale-exponential family with error in variables, and an empirical Bayes (EB) decision rule is constructed by a deconvolution kernel method.

88. Bayes classification 1) three types of covariance not equal 2) three equal covariance () 3) programming line on the machine to draw three categories (or sub-interface).

89. After analyzing several theory models of inductive reasoning, we use the Bayes Theorem to prove the premise probability principle, and integrate this theory with human mental process.

90. In this paper, a method analyseis provided, which based on AR model and Bayes taxonomy.