Python load_dict_data示例

示例#1

文件： ready_sofia_ml.py 项目： fseasy/GriduationDesignCodeForTextClassification

def main(dict_data_f, out_f):
    logging.info("load dict data from '%s'" % (dict_data_f.name))
    gramlist, v_list, r, gram_n = load_dict_data(dict_data_f)
    logging.info("load dict data done .")
    logging.info("save dict data in svm format ...")
    output_vlist_in_svm_format(v_list, out_f)
    logging.info("done. saved at '%s'" % (out_f.name))

示例#2

文件： ready_sofia_ml.py 项目： memeda/GriduationDesignCodeForTextClassification

def main(dict_data_f , out_f) :
    logging.info("load dict data from '%s'" %(dict_data_f.name))
    gramlist , v_list , r , gram_n = load_dict_data(dict_data_f)
    logging.info("load dict data done .")
    logging.info("save dict data in svm format ...")
    output_vlist_in_svm_format(v_list,out_f)
    logging.info("done. saved at '%s'" %(out_f.name))

示例#3

文件： kmeans.py 项目： memeda/GriduationDesignCodeForTextClassification

def load_data_under_dictdata(dict_data_f) :
    '''
    from dict data load the gram vector list
    input > dict_data_f : file object to dict data
    return > gram_vecs : dataset , matrix format
    '''
    logging.info("loading dict data from file '%s'" %(dict_data_f.name))
    words , vec_list , r , gram_n = load_dict_data(dict_data_f)
     
    gram_mat = np.mat(vec_list)
    logging.info("loading dict data done .")
    return gram_mat

示例#4

def load_data_under_dictdata(dict_data_f):
    '''
    from dict data load the gram vector list
    input > dict_data_f : file object to dict data
    return > gram_vecs : dataset , matrix format
    '''
    logging.info("loading dict data from file '%s'" % (dict_data_f.name))
    words, vec_list, r, gram_n = load_dict_data(dict_data_f)

    gram_mat = np.mat(vec_list)
    logging.info("loading dict data done .")
    return gram_mat

示例#5

文件： ready_dimension_reduction_model.py 项目： memeda/GriduationDesignCodeForTextClassification

def main(dict_data_f , cluster_assignment_f , out_f , cluster_num) :
    gramlist , v_list , r , gram_n = load_dict_data(dict_data_f)
    r = r.tolist()[0] # r is a (1,len(gramlist)) numpy.ndarray
    assignment = get_cluster_assignment(cluster_assignment_f)
    trans_model = generate_trans_model(gramlist , assignment , r)
    save_dr_model(out_f , trans_model , gram_n , cluster_num)

示例#6

文件： view_cluster_result.py 项目： fseasy/GriduationDesignCodeForTextClassification

def main(dict_data_f , cluster_assignment_f , out_f , cluster_num) :
    gramlist , v_list , r , gram_n = load_dict_data(dict_data_f)
    r = r.tolist()[0] # r is a (1,len(gramlist)) numpy.ndarray
    assignment = get_cluster_assignment(cluster_assignment_f)
    trans_model = generate_trans_model(gramlist , assignment , r)
    save_dr_model(out_f , trans_model , gram_n , cluster_num)