learnparam.html

SVM_light是一种非常流行的支持向量机的java接口

<FONT color="green">127</FONT>    <a name="line.127"></a>
<FONT color="green">128</FONT>      public double svm_costratio_unlab;<a name="line.128"></a>
<FONT color="green">129</FONT>    <a name="line.129"></a>
<FONT color="green">130</FONT>      /* You probably do not want to touch the following: */<a name="line.130"></a>
<FONT color="green">131</FONT>    <a name="line.131"></a>
<FONT color="green">132</FONT>      /** Iterations h after which an example can be removed by shrinking. */<a name="line.132"></a>
<FONT color="green">133</FONT>      public long svm_iter_to_shrink;<a name="line.133"></a>
<FONT color="green">134</FONT>    <a name="line.134"></a>
<FONT color="green">135</FONT>      /** Size q of working set. */<a name="line.135"></a>
<FONT color="green">136</FONT>      public long svm_maxqpsize;<a name="line.136"></a>
<FONT color="green">137</FONT>    <a name="line.137"></a>
<FONT color="green">138</FONT>      /** New variables to enter the working set in each iteration. */<a name="line.138"></a>
<FONT color="green">139</FONT>      public long svm_newvarsinqp;<a name="line.139"></a>
<FONT color="green">140</FONT>    <a name="line.140"></a>
<FONT color="green">141</FONT>      /* The following are only for internal use: */<a name="line.141"></a>
<FONT color="green">142</FONT>    <a name="line.142"></a>
<FONT color="green">143</FONT>      public double svm_unlabbound;<a name="line.143"></a>
<FONT color="green">144</FONT>    <a name="line.144"></a>
<FONT color="green">145</FONT>      /** Total amount of features. */<a name="line.145"></a>
<FONT color="green">146</FONT>      public long totwords;<a name="line.146"></a>
<FONT color="green">147</FONT>    <a name="line.147"></a>
<FONT color="green">148</FONT>      /** Fraction of unlabeled examples to be classified as positives. */<a name="line.148"></a>
<FONT color="green">149</FONT>      public double transduction_posratio;<a name="line.149"></a>
<FONT color="green">150</FONT>    <a name="line.150"></a>
<FONT color="green">151</FONT>      /** Selects between CLASSIFICATION, REGRESSION, RANKING, or OPTIMIZATION mode. */<a name="line.151"></a>
<FONT color="green">152</FONT>      public long type;<a name="line.152"></a>
<FONT color="green">153</FONT>    <a name="line.153"></a>
<FONT color="green">154</FONT>      /** The level of SVM-light debugging infos. */<a name="line.154"></a>
<FONT color="green">155</FONT>      public int verbosity;<a name="line.155"></a>
<FONT color="green">156</FONT>    <a name="line.156"></a>
<FONT color="green">157</FONT>      /**<a name="line.157"></a>
<FONT color="green">158</FONT>       * Parameter in xi/alpha-estimates upper bounding the number of SV the current<a name="line.158"></a>
<FONT color="green">159</FONT>       * alpha_t is distributed over.<a name="line.159"></a>
<FONT color="green">160</FONT>       */<a name="line.160"></a>
<FONT color="green">161</FONT>      public long xa_depth;<a name="line.161"></a>
<FONT color="green">162</FONT>    <a name="line.162"></a>
<FONT color="green">163</FONT>      /** Initializes the learning parameters with the default SVM-light values. */<a name="line.163"></a>
<FONT color="green">164</FONT>      public LearnParam() {<a name="line.164"></a>
<FONT color="green">165</FONT>        this.verbosity = 0;<a name="line.165"></a>
<FONT color="green">166</FONT>        this.type = CLASSIFICATION;<a name="line.166"></a>
<FONT color="green">167</FONT>        this.predfile = new String("trans_predictions");<a name="line.167"></a>
<FONT color="green">168</FONT>        this.alphafile = new String("");<a name="line.168"></a>
<FONT color="green">169</FONT>        this.biased_hyperplane = 1;<a name="line.169"></a>
<FONT color="green">170</FONT>        this.sharedslack = 0;<a name="line.170"></a>
<FONT color="green">171</FONT>        this.remove_inconsistent = 0;<a name="line.171"></a>
<FONT color="green">172</FONT>        this.skip_final_opt_check = 0;<a name="line.172"></a>
<FONT color="green">173</FONT>        this.svm_maxqpsize = 10;<a name="line.173"></a>
<FONT color="green">174</FONT>        this.svm_newvarsinqp = 0;<a name="line.174"></a>
<FONT color="green">175</FONT>        this.svm_iter_to_shrink = -9999;<a name="line.175"></a>
<FONT color="green">176</FONT>        this.maxiter = 100000;<a name="line.176"></a>
<FONT color="green">177</FONT>        this.kernel_cache_size = 40;<a name="line.177"></a>
<FONT color="green">178</FONT>        this.svm_c = 0.0;<a name="line.178"></a>
<FONT color="green">179</FONT>        this.eps = 0.1;<a name="line.179"></a>
<FONT color="green">180</FONT>        this.transduction_posratio = -1.0;<a name="line.180"></a>
<FONT color="green">181</FONT>        this.svm_costratio = 1.0;<a name="line.181"></a>
<FONT color="green">182</FONT>        this.svm_costratio_unlab = 1.0;<a name="line.182"></a>
<FONT color="green">183</FONT>        this.svm_unlabbound = 1E-5;<a name="line.183"></a>
<FONT color="green">184</FONT>        this.epsilon_crit = 0.001;<a name="line.184"></a>
<FONT color="green">185</FONT>        this.epsilon_a = 1E-15;<a name="line.185"></a>
<FONT color="green">186</FONT>        this.compute_loo = 0;<a name="line.186"></a>
<FONT color="green">187</FONT>        this.rho = 1.0;<a name="line.187"></a>
<FONT color="green">188</FONT>        this.xa_depth = 0;<a name="line.188"></a>
<FONT color="green">189</FONT>      }<a name="line.189"></a>
<FONT color="green">190</FONT>    }<a name="line.190"></a>




























































</PRE>
</BODY>
</HTML>